Data Science Scholars
Data Science Scholars will join a university-wide initiative dedicated to advancing Data Science throughout Northwestern. Scholars will hold joint-appointments with the Northwestern Institute on Complex Systems and Data Science (NICO)—which coordinates the program—and another Research Center matching their area of expertise. Scholars are appointed to two-year terms (potentially renewable for a third year) and receive a competitive stipend, benefits package, and an individual research budget. Starting date is flexible.
At this time, due to the global COVID-19 pandemic, we are suspending our search for two data science scholars.
The two scholars, selected annually, will be appointed across a number of research areas spanning the physical, chemical, biomedical, behavioral, social, economic, information, and communication sciences. The aim of the program is to offer a unique opportunity to expand the Scholars’ domain-focused research portfolio and, simultaneously, establish their reputation as leaders in the exploding field of Data Science and Artificial Intelligence. To this end, Scholars will be offered opportunities to establish their independence and to develop their leadership skills.
Outstanding candidates interested in this program should submit applications electronically to email@example.com. Applications from women and minority candidates are especially encouraged. Applications must include:
- a CV (including a list of publications with the most important 1 to 3 publications indicated with an asterisk),
- a three-page statement of research accomplishments and plans
- a list of 3 to 5 references
Applications received by January 1st, 2020 will receive full consideration. Later applications will be considered until all positions are filled. Applicants must complete their Ph.D. requirements prior to starting date of appointment.
Information about benefits may be found at the Office of Human Resources.
Data Science Research Opportunities Matching
The Northwestern Institute on Complex Systems will be providing a service to match Northwestern faculty with undergraduate and graduate students interested in conducting data science research.
Faculty interested in recruiting Research Assistants (RAs) should enter information on their project and technical needs here.
Students interested in conducting research and being matched should enter information on their programming and data science skills, research interests, and time availability here.
If you have any trouble with the forms, please contact NICO
Faculty Research Networking Luncheons
Interdisciplinary groups of faculty meet monthly during the academic year for discussion and exploration of significant and upcoming research areas with a strong data science and analysis focus. Overall goals of this “interdisciplinary research networking” model include new faculty connections and collaborations, innovative research agendas, collaborative publications, research grant proposals, potential new and joint hires, and identification of funding opportunities and new projects.
For 2020-2021, there are 3 active groups focusing on Addressing Climate Change, Soft Matter and New Materials, and Chicago: Addressing Urban Challenges as a Community. These groups draw research-oriented faculty participants from across Schools and a wide range of different academic departments.
If you wish to participate or have additional questions about the luncheon series, please visit the Research Networking Luncheons website or contact Kristi Hubbard, Assistant Director of Planning in the Office of Administration and Planning
Data Science Fellows Program
The Data Science Fellowship for incoming students supports graduate students dedicated to the exploration of fundamental and applied advancement in data science. Data Science Fellows participate in a variety of activities, including lectures, symposia, and networking opportunities with domestic and international experts in data science.
The Fellowship offers consists of a $10,000 stipend award above the program’s standard stipend and a $2,500 research allowance.
Nomination and evaluation process
Note that applicants cannot be nominated for both the Data Science Fellowship and the incoming Ryan Fellowship.
- Directors of Graduate Studies (DGSs) of the participating doctoral programs nominate applicants whose educational background and goals match those of the Data Science Fellowship. Specifically, the applicant’s statement of purpose and/or previous research experience should demonstrate their interest and potential for data science research.
- DGSs must email a list of their program’s nominees to TGS (firstname.lastname@example.org).
- Included in the email should be a PDF of each nominees’ entire application package (one PDF per nominee). This includes scanned copies of the nominees’ application, recommendations, transcripts, and any other relevant materials such as writing samples and resumes.
- The subject line of the email must be: “Data Science Fellowship Nominees: YOUR PROGRAM”. If space limitations require sending more than one email, the subject line must also include “1 of 4”, “2 of 4”, etc. This will ensure that TGS receives all of your nominations.
- TGS will forward the applications to the Data Science Fellowship selection committee.
- The selection committee will email a list of Fellowship winners to TGS.
- TGS will inform programs of the winners. The programs should then send offer letters to the winners, including the Data Science Fellowship language that TGS supplies.
Contact email@example.com for clarification on any matter related to the program.
Data Science Nights
Data Science Nights are monthly hack nights on popular data science topics, organized by Northwestern University graduate students and scholars. Each night will feature refreshments, a talk on data science techniques or applications, and a hacking night with data science projects or learning groups of your choice. Aspiring, beginning, and advanced data scientists are welcome!
Please see more information here.
Additional information can be found on the NICO website