phd statistics berkley

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Biostatistics PhD

Many issues in the health, medical and biological sciences are addressed by collecting and exploring relevant data. The development and application of techniques to better understand such data is a fundamental concern of our program.

This program offers training in the theory of statistics and biostatistics, computer implementation of analytic methods and opportunities to use this knowledge in areas of biological/medical research. The resources of Berkeley Public Health and the UC Berkeley Department of Statistics, together with those of other university departments, offer a broad set of opportunities to satisfy the needs of individual students. Furthermore, the involvement of UCSF faculty from the Department of Biostatistics and Epidemiology also enriches instructional and research activities.

A PhD degree in Biostatistics requires a program of courses selected from biostatistics, statistics, and at least one other subject area (such as environmental health, epidemiology, or genomics), an oral qualifying examination, and a dissertation. Courses cover traditional topics as well as recent advances in biostatistics and statistics. Those completing the PhD will have acquired a deep knowledge and understanding of the MA subject areas. Since graduates with doctorates often assume academic research and teaching careers, a high degree of mastery in research design, theory, methodology, and execution is expected, as well as the ability to communicate and present concepts in a clear, understandable manner.

The PhD degree program requires 4–6 semesters of coursework, the completion of the qualifying examination and dissertation (in total, a minimum of four semesters of registration is required). Since there are no formal course requirements for the PhD, a program of courses appropriate to a student’s background and interests may be developed with a graduate adviser.

Qualifications

A Master’s degree in Biostatistics or a related field is recommended but not required for admission to the PhD program. Strongly recommended prerequisite courses are calculus, linear algebra, and statistics. Applicants admitted without a Master’s degree may be required to go through the Biostatistics MA curriculum; students can concurrently earn that degree with no additional cost or time to degree. Normative time to degree is 5 years.

Students entering with a relevant master’s degree in biostatistics or statistics must have a faculty advisor who is a member of the Biostatistics Graduate Group committing funding and mentorship support.

GRE Exemption Criteria

GRE General Test scores are required for admission to the Biostatistics PhD program however applicants are exempted from the requirement if they meet all of the following criteria:

• Completed two semesters of calculus for a letter grade and earned a grade of “B” or higher.
• Completed one semester of linear algebra for a letter grade and earned a grade of “B” or higher.
• Completed one semester of statistics for a letter grade and earned a grade of “B” or higher.
• Cumulative undergraduate GPA of 3.0 or higher.
• Overall quantitative/math GPA of 3.0 or higher.
• For students with a Master’s in Biostatistics or a related field, graduate GPA of 3.0 or higher.
• For international students: TOEFL score of 100 or higher OR IELTS score of 7.0 or higher.

Berkeley Public Health also exempts applicants who already hold a doctoral level degree from the GRE requirement.You can find more information on the application instructions page . There is a program page in the Berkeley Graduate Application where you can indicate you meet the criteria for GRE exemption. Applicants who are exempted from the GRE are not at a disadvantage in the application review process.

Many doctoral graduates accept faculty positions in schools of public health, medicine, and statistics and/or math departments at colleges and universities, both in the United States and abroad. Some graduates take research positions, including with pharmaceutical companies, hospital research units, non-profits, and within the tech sector.

Funding and Fee Remission

Prospective students who are US citizens or permanent residents can find more information about applying for an application fee waiver for the Berkeley Graduate Application. Fees will be waived based on financial need or participation in selected programs described on the linked website. International applicants (non-US citizens or Permanent Residents) are not eligible for application fee waivers.

All PhD students are fully funded (including tuition and fees and a stipend or salary) with the exception of Non-Resident Supplemental Tuition (NRST) for the second year, if applicable. NRST is typically waived after the first year of study for PhD students when they advance to candidacy. Information on applying to GSI positions for biostatistics students can be found in the Biostatistics Division student handbook .

Tuition and fees change each academic year. To view the current tuition and fees, see the fee schedule on the Office of the Registrar website (in the Graduate: Academic section).

Please contact [email protected] if you have any questions about funding opportunities for the biostatistics programs.

Diversity, Equity and Inclusion

The Division of Biostatistics is committed to challenging systemic inequities in the areas of health, medical, and biological sciences, and to advancing the goals of diversity, equity, and inclusivity in Biostatistics and related fields.

Diversity, Equity and Inclusion in Biostatistics

Admissions Statistics

Emeritus faculty, faculty associated in biostatistics graduate group.

• Peter Bickel PhD Statistics
• David R. Brillinger PhD Statistics
• Perry de Valpine PhD Environmental Science, Policy, and Management
• Haiyan Huang PhD Statistics
• Michael J. Klass PhD Statistics
• Priya Moorjani PhD Molecular & Cell Biology
• Rasmus Nielsen PhD Integrative Biology and Statistics
• Elizabeth Purdom PhD Statistics
• Sophia Rabe-Hesketh PhD Education
• John Rice PhD Statistics
• Yun S. Song PhD Statistics; Electrical Engineering and Computer Sciences
• Bin Yu PhD Statistics

• SticiGui eText
• Distractions
• Census-related
• Voting-related

Philip B. Stark | Distinguished Professor of Statistics | University of California

Berkeley, ca 94720-3860 | stark [at] stat.berkeley.edu | 510-394-5077 | @philipbstark.

My research centers on inference problems and uncertainty quantification, especially confidence procedures tailored for specific goals. I've published on causal inference, the U.S. Census, climate, clinical trials, cosmology, earthquake prediction and seismic hazard analysis, election integrity, endangered species, epidemiology, evaluating teaching, gender bias, educational technology, food web models, the geomagnetic field, geriatric hearing loss, information retrieval, Internet content filters, litigation, optimization, reproducibility and replicability, resilient and sustainable food systems , risk assessment (including natural disasters and food safety), the seismic structure of Sun and Earth, soil carbon, spectroscopy, and spectrum estimation. Methods I developed for auditing elections have been incorporated into laws in about 15 U.S. states. Methods for data reduction and spectrum estimation I developed or co-developed are part of the Øersted geomagnetic satellite data pipeline and the Global Oscillations Network Group (GONG) helioseismic telescope network data pipeline. I currently serve on the Board of Advisors of the U.S. Election Assistance Commission and the Strategic Board of Advisors of the Open Source Election Technology (OSET) Institute. Formerly, I served on the governance committee of the Association of Foragers, the Board of Directors of Verified Voting Foundation, and the Board of Directors of the Election Integrity Foundation.

I consult on topics including antitrust, truth in advertising, behavioral targeting, the U.S. Census, clinical trials, construction defects, consumer class actions, credit risk models, election contests, environmental litigation, equal protection, First Amendment protections, geochemistry, intellectual property and patents, jury selection, trade secrets, employment discrimination, food safety, import restrictions, insurance and reinsurance litigation, insurance fraud, Internet content filters, lottery fraud, mortgage-backed securities, natural resource legislation, oil exploration, pharmaceuticals and nutraceuticals, product liability class actions, public utilities, quality control, Qui Tam (whistleblower / false claims) cases, risk assessment, sampling in litigation, signal processing, torts and toxic torts, wage and hour class actions, warranties, water treatment, and white-collar crime.

SticiGui is an online introductory Statistics "text" that includes interactive data analysis and demonstrations, machine-graded online assignments and exams (a different version for every student), and a text with dynamic examples and exercises, applets illustrating key concepts, and an extensive glossary. In 2007, SticiGui became the basis of the first online course (in any subject) taught at UC Berkeley. With Ani Adhikari, I co-taught a series of introductory statistics MOOCs in spring 2013. Nearly 53,000 students enrolled in the first course, of whom more than 10,600 finished and nearly 8,200 received a certificate of completion.

Last modified 22 October 2023. P.B. Stark . statistics.berkeley.edu/~stark/index.html

Master of Arts in Statistics Program Information

Fall semester.

STAT 201A: Introduction to Probability at an Advanced Level

Distributions in probability and statistics, central limit theorem, Poisson processes, modes of convergence, transformations involving random variables.

STAT 201B: Introduction to Statistics at an Advanced Level

Estimation, confidence intervals, hypothesis testing, linear models, large sample theory, categorical models, decision theory.

STAT 243: Introduction to Statistical Computing

Concepts in statistical programming and statistical computation, including programming principles, data and text manipulation, parallel processing, simulation, numerical linear algebra, and optimization.

Fall Semester Total Units: 12

Spring Semester

STAT 222: Masters of Statistics Capstone Project

The capstone project is part of the masters degree program in statistics. Students engage in professionally-oriented group research under the supervision of a research advisor. The research synthesizes the statistical, computational, economic, and social issues involved in solving complex real-world problems.

STAT 230A: Linear Models

Theory of least squares estimation, interval estimation, and tests under the general linear fixed effects model with normally distributed errors. Large sample theory for non-normal linear models. Two and higher way layouts, residual analysis. Effects of departures from the underlying assumptions. Robust alternatives to least squares.

Approved Elective

Spring Semester Total Units: 12

• Program Requirements
• Comprehensive Exam
• Thesis Option
• Third Semester Option

The program is for full-time students and is designed to be completed in two semesters (fall and spring).  In order to obtain the MA in Statistics, admitted MA students must complete a minimum of 24 units of courses and pass a comprehensive examination.

In the first semester, all students will take intensive graduate courses in probability, theoretical statistics, and statistical computing; the typical courses are STAT 201A, 201B, and 243. In the second semester, students will take an advanced course in modern applied statistics (STAT 230), an elective, and a capstone course. The capstone will consist of a team-based learning experience that will give students the opportunity to work on a real-world problem and carry out a substantial data analysis project. It will culminate with a written report and an oral presentation of findings. The elective will depend on the student’s interests and will be decided in consultation with advisers. For a complete list of courses offered by the department and course descriptions, please visit the academic guide .

All coursework used for the M.A. must be letter graded unless the course is only offered on a satisfactory/unsatisfactory (S/U) basis. The total of S/U units may only be 2

Elective courses are chosen with the guidance and approval of the MA program Chair. Generally, the elective must be a graduate level course related to statistics. Such courses can be within the Statistics Department or from other departments. Some examples of popular past electives:

• STAT 248: Analysis of Time Series
• STAT 254: Modern Statistical Prediction and Machine Learning
• STAT 260: Topics in Probability and Statistics

If an elective that you would like to take is not on the list the course can be submitted for department approval. You can submit your request using the Google Form here . If you take an approved elective that is less than 4 units you will need to take another elective and/or approved seminar course to meet the 24 unit minimum requirement for the program. *Approved electives are subject to change.

In extremely rare cases, a thesis option may be considered by the M.A. Chair. Typically, this will be when either the option has been offered to the student at the time of admission, or if the student arrives with substantial progress in research in an area of interest to our faculty. If approved by the M.A. Chair for the thesis option you will not have to take the comprehensive exam.

If approved for the thesis option, you must find three faculty to be on your thesis committee. Though not required, it is strongly encouraged that one of the faculty be from outside the Statistics Department. Both you and the thesis committee chair must agree on the topic of your thesis. Please provide a short description of your thesis topic, the names of your committee members and the signature of your committee chair on the Worksheet for the MA in Statistics, Thesis Option . In addition, you will also need to complete Graduate Division’s Application for Candidacy for the Master's Degree (Plan 1 - Thesis)

Professional Development

Prepare for a career in statistics with our Professional Development resources. Workshops, alumni insights, and individual advising sessions are available to help you succeed.

Summer Prep Program

Equip yourself for your MA Statistics journey with our intensive 2-week Summer Prep Program. Strengthen your mathematical foundations, explore statistical concepts, and dive into probability theory

Will I be able to take courses other than those that are required?

Course selection will be done in consultation with Statistics Department MA Chair and/or committee member. Some students do take additional courses, including courses in other departments, depending on their background and level of preparation. Other professional graduate programs on campus all have their own policies for enrollment in their courses. After appropriate consultation, students will need to check these policies before registering for such courses.

Can I transfer to the PhD program?

There is no transfer arrangement into the PhD program. To gain acceptance into the PhD program, you must apply along with all other applicants, and you will be considered in the same way as other applicants. Students should know that admission to the UC Berkeley Statistics PhD program is highly competitive.

How to Advance to Candidacy

All coursework for the MA must be completed by the end of the semester in which you intend to graduate. In order to advancement to candidacy, you need to complete the MA Statistics Comprehensive Exam and completed all the required MA coursework. For those approved by the MA Program Committee Chair, to apply for the MA thesis option, you will have to submit individual application for advancement that lists the proposed committee for the thesis through CalCentral.

If you already have a master's degree from any institution including UC Berkeley and are applying for advancement to candidacy for a master's degree in Statistics, you must:

• Provide a transcript (unofficial one)

Please submit your completed paperwork to the Master's Program Coordinator at 367 Evans Hall for review by the MA Program Committee. The department deadline to turn in paperwork is by the end of the third week of the semester in which you plan to graduate.

How do I add/drop classes or change my grading option between letter grading and satisfactory/unsatisfactory (SU)?

Each semester, graduate students have till the Friday of the third week of classes to add/drop courses on Cal Central. If you want to add/drop courses after the third week, you will have to complete a form called the Graduate Petition to Change Class Schedule . After completing the form, please submit it to the Master's Program Coordinator in 375 Evans so that it can be processed. The form can be given in person or put in the MA Program Coordinator's mailbox in 367 Evans. It must be submitted before the last day of classes in each semester, which occurs before the week of final exams.

Student Life

For information about graduate student life and housing options, please visit Resources & Services for Graduate Students and the Statistics Graduate Student Association .

International Students

What is the proportion of international students for this program.

We do not admit students based on national origin and we do not have fixed proportions of domestic and international students. The city of Berkeley and the Department of Statistics have always had a diverse and lively international community.

For questions regarding visas, employment of international students, or any other questions regarding temporary stay in the United States, please visit the Berkeley International Office Website or call them at (510) 642-2818 .

Is the MA Statistics Program a STEM OPT eligible program?

Yes, the MA Statistics program is eligible for the STEM OPT extension. The program is falls under CIP code "Statistics, General 27.0501" as of July 12, 2023.

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The School of Information offers four degrees:

The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world.

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The Master of Information and Cybersecurity (MICS) is an online degree preparing cybersecurity leaders for complex cybersecurity challenges.

Our Ph.D. in Information Science is a research program for next-generation scholars of the information age.

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Research by faculty members and doctoral students keeps the I School on the vanguard of contemporary information needs and solutions.

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Ph.D. Admissions

Next start date: August 2025

Application Deadline: December 4, 2024, 8:59 pm PST

We welcome students from a diverse set of backgrounds; some will be technically educated, some educated in the humanities and social sciences.

All application materials must be received by the deadline. We encourage you to apply early. The I School’s Ph.D. program does not accept applications for spring term admissions.

Admissions Requirements

• A bachelor’s degree or its recognized equivalent from an accredited institution
• Superior scholastic record, normally well above a 3.0 GPA
• Indication of appropriate research goals, described in the Statement of Purpose
• For applicants whose academic work has been in a language other than English, the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS)
• Not required: GRE/GMAT . Starting Fall 2021, we no longer require the GRE or GMAT. We recommend you put your time and effort towards the required application materials. Read more about our decision to drop the GRE/GMAT requirement .

Selection Criteria

The I School accepts 3–7 Ph.D. students each year from more than 100 applications. Applications are reviewed by a committee of faculty.

Applicants are evaluated holistically on a number of factors. A strong academic record is important, but not sufficient. A critical factor is the ability to demonstrate a research record and agenda that fit well with specific I School faculty. In a small, interdisciplinary program, it is important that applicants clearly indicate in their Statement of Purpose which faculty member(s) they are interested in researching with, and why.

Application Requirements

We encourage you to check out our Ph.D. Admissions FAQ for information about commonly asked application questions.

(1) Statement of Purpose & Personal History Essay

The Statement of Purpose and Personal History are two separate essays.

The Statement of Purpose should describe your aptitude and motivation for doctoral study in your area of specialization, including your preparation for this field of study, your academic plans and research interests, and your future goals. Please be sure to identify in your Statement of Purpose which faculty member(s) you are interested in researching with, and why. We expect that candidates are able to demonstrate a research record and agenda that fit well with specific I School faculty.

For additional guidance, please review the Graduate Division's Statement of Purpose Guide .

In addition to explaining how your personal experiences have influenced your decision to pursue graduate studies, your Personal History Essay may include any relevant information describing barriers to accessing higher education that you have overcome, efforts you have made to advance equitable access to higher education for women, racial minorities, and other groups historically underrepresented in higher education, or research that you have undertaken that focuses on underserved populations or related issues of inequality.

For additional guidance, please review the Graduate Division’s Personal Statement Guide . There is no minimum length for the Personal History Essay.

These two essays are used in part to evaluate the candidate’s writing skills. Pursuant to UC Berkeley policy, the statements must be written by the candidate her or himself. For admitted students, application materials must comply with the Code of Student Conduct .

Both essays should be uploaded as PDF documents, as part of the online application .

(2) Three Letters of Recommendation

Ph.D. applicants should provide letters which speak directly to their ability and potential to perform academic research at the doctoral level. Recommenders must submit their letters online; please follow the instructions in the online application .

(3) Current Curriculum Vitae

Please upload a current curriculum vitae (C.V.) as a PDF document as part of the online application .

(4) College Transcripts

As part of the online application, upload copies of the official transcripts or academic records for all university-level studies you have completed abroad and at U.S. institutions. Be sure to include a current transcript from every post-secondary school that you have attended, including community colleges, summer sessions, and extension programs.

Each transcript should be uploaded as a separate PDF document; please refer to the instructions on the online application .

Applicants who completed their undergraduate degree in a recognized academic institution outside the United States are required to upload a copy of their degree conferral certificate. If a degree conferral certificate has not yet been obtained, please upload a provisional certificate. Applicants who have not yet graduated from undergrad are not required to submit a provisional certificate at this time. For specific questions, please contact the School of Information at [email protected] .

(5) TOEFL or IELTS Scores

UC Berkeley Graduate Division requires that applicants who received their degrees in countries other than the U.S., U.K., Australia, or English-speaking Canada submit TOEFL (Test of English as a Foreign Language) or IELTS (International English Language Testing System) scores. This includes applicants with degrees from Bangladesh, Burma, Nepal, India, Pakistan, Latin America, the Middle East, North Africa, the People’s Republic of China, Taiwan, Japan, Korea, Southeast Asia, and most European countries. Only applicants who have completed a full year of U.S. university-level coursework with a grade of B or better are exempt from this requirement.

For students taking the TOEFL, UC Berkeley Graduate Division requires that your most recent score be at least 90 on the Internet-based version of the TOEFL.

For students taking the IELTS, UC Berkeley Graduate Division requires that your most recent score be at least 7.0 out of 9.0 on the IELTS Academic test.

UC Berkeley Graduate Division does not accept TOEFL ITP Plus for Mainland China, IELTS Indicator, or Duolingo scores. For more information, see  Graduate Division’s Evidence of English Language Proficiency .

Submitting Scores

To be valid, the TOEFL or IELTS must have been taken within the past 18 months: for applicants for Fall 2025 admission, test scores taken before June 2023 will not be accepted. Please have your test scores sent directly to UC Berkeley by the testing authorities prior to application submission, and at the latest, by the application deadline. It may take 10-15 days for official score reports to transfer to our system. For the TOEFL exam, the school code for UC Berkeley is 4833, and the department code for the I School is 99.

For the IELTS exam, please submit an electronic report from the testing center; no institution code is required. Here is the Graduate Division’s office address for identification purposes: University of California, Berkeley, Graduate Division, Sproul Hall Rm 318, MC 5900, Berkeley, CA 94720.

More information: TOEFL website ; IELTS website

(6) Application Fee

(submitted with the online application)

• Fee for domestic applicants: $135.
• Fee for international applicants: $155.

Application Fee Waiver : The I School is pleased to offer application fee waivers to eligible Ph.D. applicants. Prior to submitting your application, please complete our Application Fee Waiver request form , and we will contact you within two business days with further instructions.

All application materials must be received by the application deadline. Applications will be reviewed throughout December and January, and admissions decisions will be released by early February.

Please don’t hesitate to contact us with questions or for additional guidance: [email protected] or (510) 664-4742.

*Test Report Form must be sent directly from IELTS. IELTS Indicator scores are not accepted.

Computer Ownership Requirement

We require that students own a computer. No particular configuration or operating system is required. However, students will be expected to complete assignments using office productivity software (e.g., Microsoft Office, OpenOffice, etc.), web browsers, etc., and should own a computer capable of running such software. More specific guidance will be provided upon acceptance to the program.

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Ph.D. Applicant Feedback Program

The I School Ph.D. Applicant Feedback Program is a student-run initiative that aims to assist underrepresented students with their application essays and C.V. as they apply to the UC Berkeley School of Information Ph.D. program.

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No matter if you are exploring the fields of business, science, technology, economics or social sciences, the importance of enrolling in a math or statistics class goes well beyond just numbers. It equips you with a rational and organized way of thinking and problem-solving, enabling you to tackle challenges with a logical approach.

By taking our courses, you earn credits that can be transferred toward meeting the math and statistics prerequisites for your undergraduate or graduate studies. Or take a class to meet a prerequisite requirement for a non-degree program, such as our data analytics and data science programs.

Whether you aim to graduate on time or enhance your application for an advanced degree—master's or doctoral programs—our courses are designed to meet your academic and professional requirements. Looking to change your career or prepare for a promotion? Boost your résumé with a math and stats course, such as Math for Management or Calculus 1 !

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Our program curricula are designed to teach theory and practical skills to enable you to change careers or advance in your current position. Classes are offered in classroom and multiple online formats to meet the needs of working professionals. Most programs can be started at any time.

Our program curricula are designed to teach theory and practical skills to enable you to change careers or advance in your current position. Classes are offered in classroom and multiple online formats to meet the needs of working professionals.

Offered in a variety of subject areas, classes give you the flexibility to gain a high-quality education and earn credits on your schedule. Choose from multiple formats to meet your needs. Enroll in just the course or courses that interest you—no application necessary.

Offered in a variety of subject areas, classes give you the flexibility to gain a high-quality education and earn credits on your schedule. Choose from multiple formats to meet your needs.

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Statistical Reasoning Requirement

The Statistical Reasoning requirement is designed to ensure that students graduate with basic understanding and competency in inference and prediction. The requirement may be satisfied by exam or by taking an approved course. Coursework used to satisfy Statistical Reasoning must be completed with a letter grade of C- or higher.

Satisfying Statistical Reasoning with an Exam

Satisfying the statistical reasoning requirement with a berkeley course.

The following Berkeley course options, completed with a letter grade of C- or higher, satisfy the Statistical Reasoning requirement:

Satisfying the Statistical Reasoning Requirement with a CDSS major

The Statistics and Data Science major programs automatically satisfy Statistical Reasoning through their major requirements.

Satisfying Statistical Reasoning Requirement with a Transfer Course

All transfer courses pursued for Statistical Reasoning must be completed with a C- or higher. 

Students can complete a pre-approved Statistical Reasoning course at a California Community College. Pre-approved courses can be found on ASSIST . Refer to the CDSS Transfer Credit webpage for instructions on how to take transfer credit as a CDSS student before enrolling at a California Community College.

Successful completion of transferable courses from other higher education institutions (i.e., 2-year or 4-year campus in the U.S. or non-UCEAP courses from abroad) may also be considered. Course descriptions and syllabi will be required to make a determination. For more information on pursuing transfer courses for Statistical Reasoning at another higher education institution, review CDSS’s Transfer Credit: Other Higher Education Institutions webpage. 

Print Options

When you print this page, you are actually printing everything within the tabs on the page you are on: this may include all the Related Courses and Faculty, in addition to the Requirements or Overview. If you just want to print information on specific tabs, you're better off downloading a PDF of the page, opening it, and then selecting the pages you really want to print.

The PDF will include all information unique to this page.

• Computer Science
• Undergraduate Program

Introduction to the Major

The Computer Science major (CS) deals with computer theory, methods of information processing, hardware and software design, and applications. The major combines a rigorous technical program with background in the liberal arts and sciences. The CS major prepares students for technical careers or graduate school programs related to EECS or CS. 

All students admitted to the College of Letters & Science are admitted as undeclared students. To declare CS, students must achieve a cumulative grade point average of 3.30 in CS61A, CS61B, & CS70. All students who meet this criteria are admitted into the major.

One Department, Two Programs 

There is no difference in the CS course content between the CS and EECS majors--the differences are what other subjects you'd like to study and the admissions processes to the university and majors.

If you prefer greater flexibility in your coursework, or have an interest double-majoring in an area outside engineering, the CS major might be a good choice. There is greater opportunity to explore other departments, like economics, business, and music.

If you have a great interest in electrical engineering or in double-majoring in another engineering major, the EECS major may be better suited for you.

Related Majors

There are many ways to get exposure to CS other than via the CS major. The following majors are avenues to study CS and to help prepare students for industry and graduate school: applied math, cognitive science, data science, & statistics.

The CS minor is also a great option that equips students for industry and graduate school.

CS isn’t something I could’ve done alone, so I’m grateful for the community here. Steven Tan, CS student and CS Peer Advisor

• Four-Year Student Timeline

Explore Your Major

• See CS requirements & declaration policies
• Take CS10 and/or CS8 before CS61A, if no coding experience.
• See math requirements & AP/IB policies . Find calculus starting point .
• Check in with a CS major advisor .

Connect and Build Community

• New to CS? Apply for the CS Scholars Program
• Get support in classes from resources and counselors
• Become familiar with Disabled Students’ Program , Gender Equity Resource Center , Undocumented Student Program , Educational Opportunity Program .

Discover Your Passions

• Enroll in a Freshman & Sophomore Seminar . Look for CS/EE 24 & 39.
• Visit the Office of Undergraduate Research and Scholarships to learn about research opportunities. 
• Take a  DeCal , a student-facilitated course.

Engage Locally and Globally

• Explore study abroad options now so you can incorporate them into your sophomore or junior year plans.
• Explore volunteer opportunities on campus.

Reflect and Plan Your Future

• Develop a plan for getting career ready.
• Join Handshake for Berkeley-specific career opportunities.
• Learn about career opportunities in CS at  Berkeley Career Engagement .
• Look for internship programs at various companies specific to first-year students.

Second Year

• Complete the CS prerequisite coursework to declare your major. Recommended: Apply to CS by the end of your 2nd year.
• Use the EECS website to help guide your B.A. program, and the HKN course guide to think about future classes in CS/EE.
• Consider a minor .
• Learn about EECS student organizations
• Consider becoming an Academic Intern, Reader, or Tutor for a lower-division CS/EE class.
• Seek CS Peer Advising and ask questions on the EECS 101 on Edstem
• Go to office hours of professors and GSIs.
• Assist a professor in their research through the Undergraduate Research Apprenticeship Program
• Attend the EECS Department Colloquium Series to learn more about the field.
• Learn more about research opportunities available at UC Berkeley.
• Explore study abroad options for CS and meet with both a CS major advisor and your L&S advisor to confirm requirement fulfillment.
• Join Bridging Berkeley to become a math mentor to middle schoolers.
• Subscribe to the eecs-ugrad-jobs list-serv to learn about CS Info-sessions and Tech Talks
• Attend the EECS Internship Fair , EECS & STEM Career Fairs
• Meet with Berkeley Career Engagement or UPE for resume help and interview practice.
• Complete CS lower-division requirements ; begin taking upper-division courses
• Check-in with a CS major advisor
• Participate in faculty advising each semester once declared.
• If eligible and interested in research, consider the  EECS Honors Program .
• Enjoy teaching and/or mentoring? Become an EE/CS DeCal facilitator or CS Mentor . Learn about how to become an Undergraduate Student Instructor in future semesters.
• Consider applying to the Accel Scholars Program .
• Explore Beehive and other EECS research opportunities for undergraduates.
• Learn about upper-division technical electives for your major outside CS.
• Join CalTeach to gain teaching skills and explore a career in education.
• Interested in community outreach? Check out the opportunities available in community outreach programs for engineering students.
• Get matched with a graduate student mentor through Berkeley Connect .
• Attend the Engineering and Tech Career Conference to prepare for recruiting season.
• Utilize job board tools in your job search.
• Explore graduate school options by speaking with faculty members and advisors .

Fourth Year

• Complete remaining CS upper-division requirements
• Consider getting faculty permission to take CS graduate courses.
• Meet with a CS advisor to ensure CS requirements will be completed.
• Check-in with an L&S advisor to stay on track to graduate.
• Give back by becoming a CS peer advisor or tutor at the Student Learning Center .
• Volunteer for EECS Departmental events like CS Education Day and Cal Day .
• See ways to stay in touch with the EECS Department after you graduate.
• Carry out your own research project funded by scholarships
• Attend events at the Sutardja Center for Entrepreneurship & Technology or the Jacobs Institute for Design and Innovation .
• Consider researching and applying for scholarships available to recent Berkeley graduates.
• If interested in graduate school, explore gap year opportunities prior to embarking on your next academic or career adventure.
• Continue to attend industry-related events.
• Take the GRE & seek letters of recommendation if interested in graduate school.
• View the First Destination Survey to find out what recent grads are doing.

What Can I Do With My Major?

Jobs and employers.

• Analyst, Axioma
• Application Developer, Workday
• ASIC Engineer, Nvidia
• Assoc. Publishing Producer, Google
• Care Coordinator, YoDerm
• Consultant, Bain and Company
• Cyber Security Consultant, Deloitte
• Data Analyst, Apple
• Data Scientist, Nerdwallet
• Front End Developer, HealthTap
• Hardware Engineer, Apple
• Infrastructure Engineer, Capital One
• Investment Engineer, Bridgewater
• iOS Engineer, Mozilla
• Machine Learning Engineer, eBay
• Mobile Developer, Sony
• Performance Engineer, Splunk
• Program Manager, Microsoft
• Programmer, Intl CS Institute
• R&D Engineer, Glint Photonics
• Site Reliability Engineer, Google
• Software Developer, Expedia
• Software Engineer, AirBnB
• Surface Warfare Officer, U.S. Navy
• Systems Specialist, Salesforce
• Teacher, Teach for India
• Technology Analyst, Goldman Sachs
• UX Designer, GoDaddy

Graduate Programs

• Algebra & Numbers Theory
• Artificial Intelligence & Robotics
• Audiology & Hearing Sciences
• Biological Sciences
• Biostatistics
• Computational Mathematics
• Computer Engineering
• Computer Graphics
• Electrical Engineering
• Industrial & Org. Psychology
• Interdisciplinary Studies
• Physical Chemistry

Examples from the First Destination Survey of recent Berkeley graduates.

Connect With Us

Come to Berkeley’s annual Open House in April for information sessions, campus tours, special talks, and more. See what events the EECS Department offers at eecs.berkeley.edu/academics/undergraduate/calday .

Golden Bear Orientation

Join your peers in the campus-wide UC Berkeley orientation program for all new students.

Attend department events with students, staff, and faculty. Visit eecs.berkeley.edu for news and updates.

Prospective students can make an appointment to meet with a CS advisor at berkeleycs.youcanbook.me . Current students should make a CS advising appointment through CalCentral.

Drop-in CS advising is available. Please check eecs.berkeley.edu/resources/undergrads/cs/advising   for the latest schedule.

Letters & Science College advising services can be found at lsadvising.berkeley.edu

How to Use this Map

Use this map to help plan and guide your experience at UC Berkeley, including academic, co-curricular, and discovery opportunities. Everyone’s Berkeley experience is different and activities in this map are suggestions. Always consult with your advisors whenever possible for new opportunities and updates.

• What Can I Do with My Major?

Download the PDF Print Version

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• + About LAEP
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• For Students

PhD candidate wins two prestigious fellowships for research into road safety in the age of Uber Eats

Cheng-Kai (Kai) Hsu's findings highlight the need for regulatory oversight to protect vulnerable gig workers and the public.

Cheng-Kai (Kai) Hsu, a PhD candidate in the Department of City & Regional Planning, has been honored with two prestigious fellowship awards: the Institute of Research on Labor and Employment Dissertation Fellowship and the Roselyn Lindheim Award in Environmental Design and Public Health. The IRLE Dissertation Fellowship recognizes Kai’s research into occupational road safety among those working in Taiwan’s on-demand food-delivery sector. The Roselyn Lindheim Award supports his interdisciplinary investigation into the impact of urban heat on increasing road traffic injury risks in Taiwan and Latin America.

Kai’s dissertation, tentatively titled “Heat Exposure and Road Safety in the Era of a Changing Climate and the Precariousness of the Gig Economy: Evidence from Taiwan and Latin America,” explores the complex interplay between road safety dynamics, global warming, and the evolving gig economy. Utilizing wearable sensors, AI image recognition, and advanced biostatistical techniques, he aims to understand how factors like high heat exposure and precarious work structures contribute to traffic injuries and risky driving behavior.

Spanning six cities in Taiwan and 272 cities in Latin America, Kai's research has policy implications for the enhancement of road safety in tropical regions. Gig economy workers in these areas often use motorcycles, whose open designs offer little physical protection and expose their riders to high heat. In addition, the gig economy business model may exacerbate risky driving behaviors such as speeding, harsh acceleration, and tailgating, among food-delivery workers. Kai's findings point to the urgent need for regulatory oversight to safeguard the road safety of this vulnerable occupational group and the general public.

This recognition and the accompanying support significantly strengthen Kai's dissertation research as he enters his last  year of the PhD program.

Biostatistics PhD

Many issues in the health, medical, and biological sciences are addressed by collecting and exploring relevant data. The development and application of techniques to better understand such data is the fundamental concern of the Group in Biostatistics. The program offers training in theory of statistics and biostatistics, the computer implementation of analytic methods, and opportunities to use this knowledge in areas of biological/medical research. The curriculum is taught principally by members of the Division of Biostatistics (School of Public Health) and the Department of Statistics (College of Letters & Science) and provides a wide range of ideas and approaches to the analysis of data.

Established in 1955, the Graduate Group in Biostatistics curriculum offers instruction in statistical theory and computing, as well as opportunities to rigorously apply this knowledge in biological and medical research. The degree programs offered (listed below) are appropriate for students who have either a strong mathematical and statistical background with a focus in the biomedical sciences, or degrees in the biological sciences with a focus in mathematics and statistics. (The MA degree can be obtained under Plan I or Plan II. The PhD dissertation is administered according to Plan B.)

Master of Arts (MA)

The Masters of Arts Degree in Biostatistics is completed in 4 semesters. Candidates for this degree are expected to earn 48 units with courses in biostatistics, statistics, public health, and biology. Students pursuing the MA degree in Biostatistics will be expected, upon completion of the program, to be well-versed in the following areas:

Understand the foundations of statistical inference, e.g., maximum likelihood estimation, regression.

Have grounding in theoretical framework and ability to apply existing estimators in following categories:

Computational statistics

Multivariate analysis

Categorical data analysis

Survival analysis

Longitudinal data analysis

Causal inference

Clinical trials

Statistical genomics

Statistical computing

Have fluency in statistical programming languages for both analysis using classic methods and implementation of novel methods.

Identify and apply sound and pertinent methods to address statistical inference questions in biological, public health, and medical research.

Effectively communicate research findings, orally and in writing.

Doctor of Philosophy (PhD)

All Biostatistics PhD students are required to hold a master's degree in Biostatistics or a related field. The PhD degree requires 4-6 semesters of course work in biostatistics, statistics, and at least one other subject area (e.g., biology, environmental health, epidemiology). There are no unit or course requirements for the PhD, so a program of courses appropriate to a student's background and interests may be developed. Courses cover traditional topics as well as recent advances in biostatistics and in statistics. Those completing the PhD will have acquired a deep knowledge and understanding of these subject areas. Since graduates with doctorates often assume academic careers in research and teaching, a high degree of mastery in research design, theory, methodology, and execution is expected as well as the ability to communicate and present research findings and area of expertise in a clear, understandable manner.

Many doctoral graduates accept faculty positions in schools of public health, medicine, and statistics and/or math departments at colleges and universities, both in the United States and abroad. Some graduates take research positions, including with pharmaceutical companies, hospital research units, non-profits, and within the tech sector.

Biostatistics Doctor of Philosophy (PhD) with Designated Emphasis (DE)

Students enrolled in the UC Berkeley Biostatistics doctoral (PhD) program are eligible to apply for interdisciplinary study in a Designated Emphasis (DE), which we refer to as the Associated Programs. At UC Berkeley, acquiring a DE is like earning a "minor" with a PhD degree. Applications for Designated Emphasis are reviewed on a rolling basis throughout the year. However, students must apply prior to taking the qualifying exam and are strongly encouraged to begin the application process early in the third semester of graduate study. To be accepted to a Designated Emphasis, you must be a PhD candidate in one of the Associated Programs (e.g., Biostatistics). The two DE programs offered in biostatistics are:

• Designated Emphasis in Computational and Genomic Biology (DE-CGB)
• Designated Emphasis in Computational Science and Data Science and Engineering (DE-CSDE)

The goal of the DE-CGB program is to train a new generation of computational biology researchers by enhancing and facilitating interactions between faculty, postdoctoral scholars and students in the Associated Programs through a flexible and integrated research and teaching environment which transcends traditional departmental boundaries. Upon successful completion of all requirements and dissertation, your transcript and diploma will read, "PhD in Biostatistics with a Designated Emphasis in Computational & Genomic Biology."

The DE in Computational Science and Engineering (CSE) promises to bring a new paradigm to interdisciplinary research and education. The team-oriented approach provides our students with a solid foundation in the different facets of genomic research and ensuing competitive edge for the most desirable jobs in academia and industry, which increasingly require interdisciplinary training by combining high-performance computing, mathematical modeling, scientific and engineering theory, and analysis of large scale databases of observations. Upon successful completion of all requirements and dissertation, your transcript and diploma will read, "PhD in Biostatistics with a Designated Emphasis in Computational Science and Engineering."

Contact Info

[email protected]

2121 Berkeley Way West, 5th floor

Berkeley, CA 94720

At a Glance

Department(s)

Biophysics Graduate Group

Admit Term(s)

Application Deadline

December 4, 2023

Degree Type(s)

Doctoral / PhD

Degree Awarded

GRE Requirements

• Equity & Inclusion

Joint California Summit on Generative AI

Advancing GenAI Leadership & Collaboration May 29, 2024 | Live-streaming at 9:00 am Pacific Time

To access the captioned livestream, please use this link:  https://youtube.com/live/Qbm2iC0_7hg

Highlighted in Governor Newsom's Executive Order , the Joint California Summit on Generative AI will focus on how the State can best use Generative AI to better serve the people of California and the impacts of GenAI on California and its workforce. 

AI is profoundly changing how we learn, communicate, and engage with the world. We invite you to join us for timely discussions and dynamic, thought-provoking panels that will livestream right here on May 29, 2024 starting at 9:00 am Pacific Time. 

This summit is a joint effort between UC Berkeley’s College of Computing, Data Science, and Society (CDSS) , the Stanford Institute for Human-Centered Artificial Intelligence (HAI) , the California Governor’s Office of Business and Economic Development (GO-Biz) , and the California Government Operations Agency (GovOps) .

Event Contact

[email protected]

Media Contact

[email protected]

Gavin Newsom

Governor of California

Jennifer Chayes

Dean, UC Berkeley College of Computing, Data Science, and Society 

Denning Co-Director, Stanford Institute for Human-Centered AI

Bridget Agyare

Alumni, UC Berkeley

Allison Jia

Master's Student, Stanford University

Dean’s Senior Fellow for UC Berkeley College of Computing, Data Science, and Society and former U.S. Chief Data Scientist for the White House

Jason Elliott

Deputy Chief of Staff, Office of Governor Gavin Newsom

Maryana Iskander

CEO, Wikimedia

Ann Patterson

Cabinet Secretary, Office of Governor Gavin Newsom

Louis Stewart

Head of Strategic Initiatives for NVIDIA and Board Member of the California Council on Science & Technology

Stewart Knox

Secretary, California Labor & Workforce Development Agency

Catherine Bracy

CEO, Tech Equity Collaborative

Sonya Christian

Chancellor, California Community Colleges

Sara Flocks

Legislative Director, California Labor Federation (AFL-CIO)

Eraina Ortega

Director, California Department of Human Resources

Fernando Pérez

Faculty at UC Berkeley and Co-Founder of 2i2c.org and Project Jupyter

Chief Deputy Cabinet Secretary, Office of Governor Gavin Newsom

Fred Blackwell

CEO, San Francisco Foundation

Anamitra Deb

Managing Director of Responsible Technology, Omidyar Network

Isabelle Hau

Executive Director, Stanford Accelerator for Learning

Zachary Pardos

Faculty, UC Berkeley School of Education

Allison Scott

CEO, Kapor Foundation

Secretary,  California Government Operations Agency

Liana Bailey-Crimmins

State Chief Information Officer and Director of the California Department of Technology

Robin Carnahan

Administrator, United States General Services Administration

Faculty at Stanford Law School and Senior Fellow at the Stanford Institute for Human-Centered AI

Chris Manning

Faculty at Stanford University and Senior Fellow at the Stanford Institute for Human-Centered AI

Matei Zaharia

Faculty at UC Berkeley and Co-Founder and Chief Technology Officer of Databricks

Dee Dee Myers

Senior Advisor to the Governor and Director of the Governor’s Office of Business and Economic Development

Jonathan Levin

Incoming President, Stanford University

Incoming Chancellor, UC Berkeley

9:00 am - Opening with Our Future Leaders

Bridget Agyare, alumni, UC Berkeley

Allison Jia, student, Stanford University

Jennifer Chayes, Dean, UC Berkeley College of Computing, Data Science, and Society 

Fei-Fei Li, Denning Co-Director, Stanford Institute for Human-Centered AI

9:30 am - 10:15 am

California’s opportunity landscape.

Moderator: DJ Patil, Dean’s Senior Fellow for UC Berkeley College of Computing, Data Science, and Society and former U.S. Chief Data Scientist for the White House

Jason Elliott, Deputy Chief of Staff, Office of Governor Gavin Newsom

Maryana Iskander, Chief Executive Officer, Wikimedia

Ann Patterson, Cabinet Secretary, Office of Governor Gavin Newsom

Louis Stewart, Head of Strategic Initiatives for NVIDIA and Board Member of the California Council on Science & Technology

Note: The livestream will pause at 10:15 am.  

In-person (not livestreamed) working sessions will focus on: 

GenAI in Health & Medicine: Emerging Opportunities & Challenges – with Mark Ghaly, Secretary, California Health & Human Services Agency

GenAI in Climate: Accelerating Effective Collaboration & Impact – with Wade Crowfoot, Secretary, California Natural Resources Agency

GenAI in Transportation: Emerging Prototypes – with Toks Omishakin, Secretary, California State Transportation Agency  

Please join promptly at 1 pm to catch the afternoon program!  

1:00 pm - 1:45 pm

The future of the california workforce.

Moderator: Stewart Knox, Secretary, California Labor & Workforce Development Agency

Catherine Bracy, Chief Executive Officer, TechEquity Collaborative 

Sonya Christian, Chancellor, California Community Colleges  

Sara Flocks, Legislative Director, California Labor Federation (AFL-CIO)

Eraina Ortega, Director, California Department of Human Resources

Fernando Pérez, Faculty at UC Berkeley and Co-Founder of 2i2c.org and Project Jupyter

Sissy Wood, Research Director, Service Employees International Union (SEIU)

Fireside Chat:  Governor Gavin Newsom in conversation with Jennifer Chayes (UC Berkeley) and Fei-Fei Li (Stanford University)

Genai in education & learning: critical needs & paths forward.

Moderator : Ben Chida, Chief Deputy Cabinet Secretary, Office of Governor Gavin Newsom

Fred Blackwell, Chief Executive Officer, San Francisco Foundation

Anamitra Deb, Managing Director of Responsible Technology, Omidyar Network

Isabelle Hau, Executive Director, Stanford Accelerator for Learning

Zachary Pardos, Faculty, UC Berkeley School of Education

Allison Scott, Chief Executive Officer, Kapor Foundation

Additional in-person (not livestreamed) working sessions will focus on:

California as a Hub for GenAI Innovation – with Jeffery Marino, Director, Office of Data and Innovation

Responsible & Safe GenAI in Practice: From Frameworks to Implementation – with Rishi Bommasani, PhD Candidate in Computer Science at Stanford University, and Deborah Raji, PhD Candidate in Computer Science at UC Berkeley 

3:45 pm - 4:30 pm

Our innovation ecosystem and infrastructure.

Moderator: Amy Tong, Secretary, California Government Operations Agency

Liana Bailey-Crimmins, State Chief Information Officer and Director of the California Department of Technology

Robin Carnahan, Administrator, United States General Services Administration

Daniel Ho, Faculty at Stanford Law School and Senior Fellow at the Stanford Institute for Human-Centered AI

Chris Manning, Faculty at Stanford University and Senior Fellow at the Stanford Institute for Human-Centered AI

Matei Zaharia, Faculty at UC Berkeley and Co-Founder and Chief Technology Officer of Databricks

Reflections and Closing Remarks

Dee Dee Myers, Senior Advisor to the Governor and Director of the Governor’s Office of Business and Economic Development

Jonathan Levin, Incoming President, Stanford University

Rich Lyons, Incoming Chancellor, UC Berkeley

Special thanks to Kathy Kwan, Alan Eustace, and the McGovern Foundation for philanthropic seed funding to UC Berkeley CDSS and Stanford HAI to enable the Summit — and to the California Council on Science & Technology (CCST), Stanford Institute for Economic Policy Research (SIEPR), Kapor Foundation, Omidyar Network, and San Francisco Foundation for in-kind support and collaboration.

Statistics and Actuarial Science

Information for new graduate students in actuarial science, data science and statistics at the university of iowa..

Welcome New Graduate Students!

Information for NEW graduate students in Actuarial Science, Data Science and Statistics at the University of Iowa. 

Last Updated, May 31, 2024.                                   Additional  updates will be sent this summer!

Important Information for International Students

The Office of International Students and Scholars does an incredible job helping you settle into Iowa City and the University of Iowa.  They have webinars to help with:  

1. Getting Started and Making Travel Arrangements

2. Achieving Success: On-campus Involvement and Cultural Adjustment (undergraduate students)

3. Graduate Student Professionalization and Support

4. Understanding Orientation Expectations, Responsibilities, and Placement Tests (graduate students)

5. On-campus Housing Assignments and Move-in Tips (undergraduate students)

6. Student Employment

7. Money Matters - University Billing

Do you need to take the SPEC (Spoken Proficiency of English for the Classroom)?

All students for whom English is not a first language (as self-reported on their admissions application) and who have first-time appointments as graduate teaching assistants (TAs) are required to go through a testing process to assess their effectiveness in speaking English before they are assigned assistantship responsibilities. Beginning in Fall 2024, there will be a new test to assess communication in English in a classroom context called SPEC (Spoken Proficiency of English in the Classroom).  This is replacing ESPA and ELPT.  Details will be coming soon.

Any graduate student who is included in the following categories needs to have their oral English proficiency tested by the TAPE Program:

• Students whose first language is not English (i.e., learned another language first) as self-reported on their admissions application, and
• Have been appointed as a Teaching Assistant

Exemptions (may change):

• Students with an official valid (within the last two years) iBT Listening score of 25 and an iBT Speaking score of 26.
• Undergraduate degrees and/or     
• Continuous attendance of English-language schools since the age of 12 (or younger)
• Students who served as teaching assistants at other institutions of higher learning in which the language of instruction is English, if they were listed as the instructor of record for a course or led a discussion section in English for at least one year, with a year defined as either two academic semesters or three academic quarters.
• Requests for exceptions regarding the SPEC  can be submitted for evaluation to a committee consisting of the Director of ESL Programs, the Associate Dean for Administrative Affairs in the Graduate College, and a representative from University Human Resources.

Requests for exemption and exceptions must come from the department by the deadline, not the student.   Deadlines to register students for the SPEC are:

• March 1  

NOT Exemptions:

• Students who come from a country where English is one of the official languages.
• Students who are U.S. permanent residents or U.S. citizens whose first language is not English.

Testing Procedures & Results

 To be announced soon!

Graduate/Professional International Students Important Dates

July 12, 2024:  Earliest date you may enter the U.S. in F-1 or J-1 status. August 11, 2024:  Latest date by which you should arrive in Iowa City August 12 - 16, 2024: International Student Orientation August 26, 2024:  Classes begin.

Housing Information for All Students

The department has a housing webpage, please let us know if you have any questions or concerns. If you are looking for a roommate, please let us know and we can update this web page!

Looking for housing options ?

All US citizens that are financially supported (TA, RA) need to be here on August 21.

All students will register for classes the week before classes start.  International students must complete the required Orientation Program before  they can register for classes.    

____________________

Fall Classes Advising will be August 19-23

All NEW UI students must meet with their advisor prior to registration.  There is no worry about getting into any of the classes we teach.  

• IF you are an Actuarial Science MS or PhD student you will need to meet with Professor Shyamalkumar.  Email him after August 12 at [email protected] to set a time to meet to discuss what classes to take, it may be on Zoom or in his office (233 Schaeffer Hall).
• IF you are a Data Science MS, Statistics MS, or PhD student you will need to meet with Professor Boxiang Wang.  Email him after August 12 at [email protected]  to set a time to meet to discuss what classes to take, it may be on Zoom or in his office (261 Schaeffer Hall).

New Graduate College Welcome and Orientation, August 21

The Graduate College Fall 2024 Graduate Student Orientation event will take place on Wednesday, August 21, 2024.  A registration form will be sent to your UI email sometime this early summer from the Graduate College. All new doctoral and master’s students are invited to attend.  

New Teaching Assistant Orientation, August 22- required for all new supported students

Sponsored by the Center for Teaching

This event will introduce participants to the role of teaching assistant at the University of Iowa and prepare them for the first week of classes and beyond. 

Participants will discuss evidence-based teaching strategies for lesson planning, inclusive teaching, and more with Center for Teaching staff. Participants will also choose two workshops of interest to them out of several options; these will be facilitated synchronously by experienced TAs.  This is a virtual event for 9-noon.

• Sign up before August 21!

New Student Department Orientation, August 23 at 9 a.m., Room to be determined.

• All New Student Orientation —Group Introductions and General Policy Procedures.

New Supported Graduate Assistants Orientation, August 23 at 1 p.m., Room to be determined.

• Our Director of Graduate Studies will have a department review of expectations and your specific roles in our department. Teaching and grading assignments will be explained, as well as preparation, teaching tips, problems and questions, quizzes and exams, weekly meetings, grading, appropriate office use and the Sexual Harassment Prevention Education

Mailbox in 241 Schaeffer Hall 

All graduate students will have a mailbox in our main office.  The faculty do as well.  Please check your mailbox at least once a week!

Office Desk Assignment

Nearly all supported students will have a desk in one of our offices.  The assignment priority (in this order) includes Ph.D. and Fellowship candidates, research assistants, half-time teaching assistants, quarter-time teaching assistants and lastly graders.  Having a desk is a privilege and should be used only for university business.  Office assignments will be given to students on, August 23.  Keys are checked out ONLY after that time.  Please remember to keep the rooms clean and take out all trash to the large bins in the main hallways.

Set-up your University of Iowa Email

All University of Iowa students are required to activate their assigned uiowa.edu email address, as all official communication from university offices are now sent via email, rather than hard copy. This address usually follows the pattern [email protected]   (However, often a number is also attached.) 

To activate the account:

• Log on to  MyUI
• Click on My UIowa / My Email / Request Email Account
• Complete the specified steps.

Students who prefer to maintain only their work or home email addresses can do so by routing the uiowa.edu email to a work or home account. To do so, follow these steps:

• Click on My UIowa / My Email / Update Email Routing Address

Important Notes:

• If your uiowa.edu email address is routed to a different account, you will  not  need to change your address in ICON, as your messages will already forward to your routed address.
• Log on to MYUI.
• Click on My UIowa / My Email / Email Account Filter bulk mail.
• Make sure that none of the categories are checked.

Required Graduate Assistants Teaching Courses:

• ONLINE CLASS Requirement: Sexual Harassment Prevention Edu.  Use your HawkID and password to log into Employee Self Service. Click the Personal tab, next (under Learning and Development) click on Sexual Harassment Prevention Edu., follow instructions.
• ONLINE CLASS Requirement:  Federal Educational Rights and Privacy Act (FERPA), Use your HawkID and password to log into Employee Self Service. Click the Personal tab, next (under Learning and Development) next click on Available Online Icon Courses, next FERPA Training, then click on View Details twice and the last click will be to Enroll in this ICON Course Session.
• A six-hour orientation program will be required of all students who are certified at level A or B and are teaching for the first time.  This orientation helps new teaching assistants understand the culture of the U.S. classroom and treats topics such as student expectations, teacher-student relationships, and understanding and answering student questions. Discussion focuses on suggestions for maximizing comprehensibility in spoken English. This course meets twice for 3 hours early in the semester. Both meetings are held in the evening.

Administrative Department Staff:

Professor aixin tan (until july 1, 2024).

Director of Graduate Studies, Statistics and Data Science Graduate Advisor: [email protected]   (319) 335-0821.

Professor Boxiang Wang (beginning July 1, 2024)

Director of Graduate Studies, Statistics and Data Science Graduate Advisor: [email protected] (319) 335-2294.

Professor N.D. Shyamalkumar

Actuarial Science Graduate Advisor:  [email protected]    (319) 335-1980

Margie Ebert

Academic Services Coordinator ,  [email protected]  (319) 335-2082

Heather Roth

Administrative Services Coordinator  [email protected]   (319) 335-0712

Tammy Siegel

Department Administrator ,  [email protected] , (319) 335-0706