Data Science Research Positions at the University of Washington

Please note: Applications for the 2105 fellowships are due by January 5, 2015.

The University of Washington eScience Institute is pleased to announce multiple new research positions as part of a multi-year Data Science Environment (DSE) partnership between UW, UC Berkeley, and NYU funded jointly by the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation. Read the press release.

The research scientist and data scientist positions are now posted on the UW Hires site.

Data Science Fellows

Driven by rapid advances in our ability to acquire and generate data, all fields of discovery are transitioning from “data-poor” to “data-rich.” The bottleneck to discovery is becoming our ability to perform inference over heterogeneous, noisy, and often massive datasets. In order to remain at the forefront, universities must lead in advancing the techniques and technologies of data-intensive discovery, and in making these techniques and technologies accessible to researchers in the broadest imaginable range of fields. The Moore and Sloan Foundations have joined with UW, Berkeley, and NYU in a collaborative experiment intended to transform the process of discovery and the institutional environments in which discovery takes place.

The UW eScience Institute is a team of interdisciplinary researchers committed to advancing these goals. Our strategy is to focus on joint programs involving methods researchers (in computer science, statistics, and applied mathematics) and domain science researchers (in the life, physical, and social sciences.)

We attract and promote top-notch interdisciplinary researchers and practitioners with backgrounds in both methods and domain science, but who may not fall neatly into conventional career paths. The successful candidates will join our team and engage in research that will advance both domain science and data science methodology: new platforms, new algorithms, new methods, and new applications. The candidates will also have opportunities, if desired, to teach short-course bootcamps, full undergraduate and courses, and will develop and run massively open online courses.

There are three types of positions available: Data Scientist, Research Scientist, and Postdoctoral Fellow. Here's how they are distinguished:

Data Scientist / Engineer

Research Scientist

Postdoctoral Fellow

Full support from the DSE Partial support from the DSE, partial support from other specific research projects. Full support from the DSE
Research position, with opportunities to publish but with emphasis on alternative metrics of impact (software uptake, etc.) Research position, with emphasis on publications as well as alternative metrics Research position, with emphasis on publications as well as alternative metrics
Intended for those seeking technical research career paths, not necessarily faculty positions Intended for those seeking technical research career paths, not necessarily faculty positions Intended for those seeking faculty positions
Works independently, with direction from DSE leadership Works independently, with direction from DSE steering committee and other stakeholders commensurate with funding sources Works independently, with direction from a team of interdisciplinary faculty advisors
Advanced degree may be typical, but not necessarily required Advanced degree may be typical, but not necessarily required Ph.D. required
Permanent space in the interdepartmental data science studio Part-time space in the interdepartmental data science studio Permanent space in the interdepartmental data science studio
Emphasis on short-term “incubator” projects, often contributing to shared cyberinfrastructure with hundreds of users. Emphasis on longer-term projects with specific science goals, and “translation” between domains Emphasis on longer-term projects with specific science goals,  and “translation” between domains
Emphasis on alternative metrics and software uptake, with opportunities to publish Emphasis on publications as well as alternative metrics Emphasis on publications as well as alternative metrics
May be PI on grants, depending on experience May be PI on grants, depending on experience May be PI on grants, depending on experience

Data Science Graduate Researchers

In addition, multiple graduate student positions are available as part of a new National Science Foundation IGERT (Integrative Graduate Education and Research Traineeship) award for an interdisciplinary Ph.D. program on data science to the same group of PIs. Read more about these positions.

While a broad range of University of Washington faculty are participating in these efforts, the principals responsible for the Moore/Sloan collaboration and the NSF IGERT award are:

Cecilia Aragon, Human-Centered Design & Engineering Bill Howe, Computer Science & Engineering
Ginger Armbrust, Oceanography Željko Ivezić, Astronomy
Magda Balazinska, Computer Science & Engineering Ed Lazowska, Computer Science & Engineering
David Beck, Chemical Engineering Randy LeVeque, Applied Mathematics
Josh Blumenstock, Information School Tyler McCormick, Statistics and Sociology
Andy Connolly, Astronomy Marina Meila, Statistics
Tom Daniel, Biology Bill Noble, Genome Sciences
Mark Ellis, Geography Thomas Richardson, Statistics
Emily Fox, Statistics Werner Stuetzle, Statistics
Dan Grossman, Computer Science & Engineering Ben Taskar, Computer Science & Engineering
Carlos Guestrin, Computer Science & Engineering Luanne Thompson, Oceanography
Jeff Heer, Computer Science & Engineering John Vidale, Earth & Space Sciences