Are students from colleges and universities other than the University of Washington eligible to apply?

Yes. You may be a student from any degree-granting college or university.

I am an incoming or prospective university student, a recent graduate, or a student at a data science boot camp. Am I eligible to apply?

Unfortunately you are not eligible to apply. Only current students at degree-granting colleges or universities may apply. You must be enrolled in a degree-granting program in the Spring 2022 term in order to be eligible to apply. 

You are, however, eligible to apply as a project lead, if you have a project you would like to propose for the program. Please see our Call for Proposals for further information.

I am an international student in the U.S., or a student at a college or university outside the U.S. What visas are required to apply for the program?

Since fellows receive a monetary stipend, international students at U.S. institutions are required to have an F1 work visa in place prior to submitting an application, and a Curricular Practical Training (CPT) work authorization in place prior to beginning the program. Please note that we do not accept Optional Practical Training (OPT) work authorization as a basis for participation. If you have an EAD work permit, you may be eligible to apply – please indicate the expiration date in your application. The University of Washington maintains this website with information about F1 regulations, but keep in mind that non-UW students must apply for work authorization from their own universities. Please contact the International Student Services office at your home institution for eligibility questions and to begin the process of obtaining work authorization.

Unfortunately, applicants with the following visas are not eligible: B1, J1, H4, or travel visas (with one exception: Canadian students with a B1/B2 visa are eligible). Fellows are not permitted to work as volunteers.

If you are a U.S. citizen attending a four-year college or university outside of the U.S., you are eligible to apply for the program and do not need a visa or work authorization to participate. 

UW cannot sponsor visas for program participants, so non-U.S. citizens attending colleges or universities outside the U.S. are not eligible to apply.

I am an undocumented U.S. student. Am I eligible to apply for the program?

Yes. Please reach out to program coordinator Emily Keller ( to discuss the logistics for participating in the program and receiving a monetary award.

What is your rate of acceptance?

Historically, we have received 150 to 200 applications from prospective student fellows each year, and most years, we have admitted 16 fellows to the program, so our acceptance rate tends to be about eight percent. Due to the remote nature of the program in 2020 and 2021 due to the coronavirus pandemic, the number of admitted students was lower.

What are the chances of undergraduates being accepted?

This program is very competitive but 20-25% of the available slots have typically gone to undergrads (only those with junior or senior standing are eligible to apply).

What will the hybrid remote/in-person program be like? 

When we say that we plan to run the program as a hybrid of remote and in-person collaboration, we mean that some projects will be run entirely remotely and other projects will be run in-person. If you are part of a remote team, then you may participate in the program from wherever you live. You will participate in all program-wide activities and team-specific activities via Zoom and other technologies that facilitate remote work. If you are part of an in-person team, then you must be located in Seattle during the Summer of 2022 and be willing and able to work from the University of Washington campus on a daily basis. While we expect that most teamwork on in-person projects will take place in the Data Science Studio, certain program-wide activities will be held remotely to accommodate the participation of individuals on remote teams. In-person plans are subject to change based on current public health guidelines and university policies. 

Do you provide support for students who need additional financial assistance to participate?

Yes. In addition to the standard stipend, all students are eligible to apply for the Micron Opportunity Scholarship, which offers financial awards to students whose circumstances pose barriers to their participation. This is intended to help with expenses such as equipment costs, disability accommodations beyond those typically covered by the University of Washington, housing costs, out-of-pocket medical expenses, childcare or dependent care costs, or other needs. For more information, see the link above.

Do you provide support for remote work set-ups?

Yes. In cases where a project is being run remotely, we will conduct a survey to assess each fellow’s remote work set-up, including hardware, internet connectivity, etc. We may be able to help mitigate challenges with the Micron Opportunity Scholarship (see also above). 

I can participate for most of the scheduled time between June 13th and August 19th, but I have other activities such as vacation, travel or conferences  planned during this time. Can I apply?

It depends. Fellows are expected to participate in program activities in-person and full-time throughout the program. Absences cannot be accommodated during the first two or final two weeks of the program (June 13 – 24 and August 8 – 19). During the middle six weeks of the program (June 27 – August 5), applicants may miss only up to two days of DSSG work for pre-planned activities. Such absences must be requested in advance. When submitting an application as a prospective DSSG fellow, you will be asked to affirm that you can comply with these attendance policies.

What level of programming experience is necessary?

We do not have rigid requirements for programming experience, and we intentionally look for a variety of technical skills. But at minimum, we expect that you should be comfortable using one programming language to solve data/software problems by quickly discovering and learning what you need to know. Strong applicants have experience coding on projects completed outside of formal introductory programming courses. Languages commonly used in our projects include Python, R, SQL and JavaScript. Prior experience with one or more of these is helpful but not required, provided you can learn new software tools quickly.

I am not sure what is meant by the question about “social good” experience in the application. What kinds of activities should be included there?

We have an open definition of “social good,” and are truly interested in hearing how you interpret this for yourself. But relevant experience might include social justice activism, civic engagement, community organizing, applied research addressing pressing social issues, work with nonprofit organizations, civic technology development, humanitarian assistance, community-based participatory research, charitable fundraising, and many other things. Relevant experience does not need to be technical in nature, nor does it need to overlap with your educational/research activities.

When will I receive a response to my application?

March 11, 2022 is our target date for notifying applicants who have been selected to advance to the interview stage of the vetting process. 

When will I know if I have been accepted into the program or not?

April 11, 2022 is our target date for making offers of admission into our program. 

What technical tools are used by the research teams?

This really varies depending on the needs of the project. Research teams have used a variety of programming languages in the past, but the most common are Python, R, and SQL. Most teams in the past have used cloud computing resources to some extent in their work. Many of our projects have a spatial analysis component and incorporate ArcGIS or QGIS. Nearly all projects involve some sort of visualization, which might involve learning tools like Matplotlib, Shiny, D3, Tableau, and others. Many teams also end up using Jupyter Notebooks for part of their workflow. The only tools that are pretty much universal across all DSSG projects are Git and Github for version control. You are not required to have expertise in any specific languages or tools to apply for the program, and we will provide tutorials on most if not all of these technologies as needed throughout the summer.

I don’t have a computer. Can I borrow one?

We expect all participants to have a personal laptop for all DSSG activities. However, if you do not have a laptop, we may be able to loan you one.

When will this year’s DSSG projects be announced? If I am selected as a DSSG Student Fellow, will I get to choose which project I will work on?

We make every effort to have projects in place prior to making offers of admission so that short-listed candidates can have the opportunity to learn a little about each project and indicate their preferred assignment.  We try to ensure that every fellow is assigned to either their first or second choice of project, but this isn’t always possible depending on how preferences are distributed across the cohort. We also consider other factors when forming teams, such as variations in education level (e.g. undergrad v. advanced graduate students), technical skills, and experience working toward social good.

How are the 10 weeks of the DSSG program structured?

The first two weeks of the program (June 13-24) have a lot of structured group activities, such as icebreakers and program orientation, essential technical tutorials, stakeholder analyses and field research events, ethics and human-centered design workshops, teambuilding sessions, and project charter development. During the rest of the program (June 27 – August 19), there are minimal structured activities for all program participants; these include a weekly “spotlight” meeting that showcases the progress of project teams and a program-wide meeting for check-ins and announcements. We also occasionally offer tutorials throughout the summer as needed. Aside from that, you will develop a regular team schedule in conjunction with your project leads, data science mentors, and possibly external stakeholders. The final week of the program will include a public presentation of your work.

For project teams that are run remotely, differing time zones will be taken into account in determining meeting times.

What can I expect to learn in the program?

In dividing the work on your project, each individual’s own learning objectives will be balanced with the needs of the team’s research question. You might get much better at certain skills you’re already bringing with you into the program, and you might learn entirely new skills as well. In the past, some of our fellows have picked up a totally new programming language, gotten familiar with cloud computing resources, trained a machine learning algorithm for the first time, etc. It’s hard to say exactly what skills you will spend your time on, as each project will be different in nature; moreover, within each team, individuals may be working on different aspects of the project. Having said that, all students can expect to learn a lot about cleaning data, developing software, using best practices in reproducible science, working in interdisciplinary and cross-sector teams, grappling with ethical questions in data-intensive work, and thinking from a human-centered design perspective. Also, you will likely be working on a project in a domain or problem space that is new to you, and you can expect to learn a lot about that subject matter.

I prefer to work independently. Are there options for working outside of a project team?

No. Teamwork is an indispensable part of the DSSG experience. Every year, fellows overwhelmingly rank working collaboratively with their teammates as one of the most impactful and rewarding aspects of the program. But it can also be challenging, and we realize that this is not the kind of challenge everyone seeks. If you know that you become stressed by things like waiting for consensus to emerge, sharing attribution for your work, or modulating your pace of work to accommodate others, then this program might not be the best fit for you.

What kind of mentorship do DSSG fellows get?

Each team will have one or two Project Leads; these are typically the individuals who proposed the project and will sustain the work after the summer is over. Each team will also have one or more Data Scientists who act as mentors; these are research scientists from the eScience Institute who provide advice on tools, methods, and software design, and sometimes provide project management support as well. The program will also have a Human-Centered Data Science Mentor; this person works across all teams to help integrate stakeholder perspectives and ensure that the work is well-documented and reproducible.

What are my obligations as a DSSG fellow?

This is a full-time (40 hour/week) time commitment, and you are expected to show up to all meetings and work alongside your teammates every business day (Mon-Fri, except holidays). You are expected to fully participate in all program activities, and to be a team player. You are expected to abide by our Code of Conduct, act ethically, use best practices in open and reproducible science whenever possible, do rigorous research, and keep the needs of your project leads and other stakeholders in mind. You will also be asked to provide input for at least one blog post about your project or your experience in the program.

Can I receive course credit for my participation in the program?

The University of Washington does not provide course credit for participation in the DSSG. However, some students in the past have used the program to fulfill internship requirements at their own universities. Those details can be worked out with your university.

Can I have someone from the eScience Institute look at my application and give me feedback before submitting? 

No. All of our research staff are involved in either reviewing applications or running the DSSG program, so they cannot provide specific feedback on application materials to particular individuals.