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Mentor Areas

Developing and applying smarter machine learning (ML) is critical to biomedical data mining and many other real world applications. The URBS-lab is focused on investigating interpretable ML and artificial intelligence methods that can select features and generate predictive/interpretable models, in the presence of complex associations. Tackling these challenges can improve our understanding of disease etiology, risk prediction, and personalized medicine.

Description:

Projects will vary. Interested students should contact us to discuss possibilities.

Preferred Qualifications

Experience with programming in Python and/or other coding languages (mastery of basics preferred, but commitment to learn welcome). Interest and/or experience in machine learning, data analysis, informatics, and/or statistics encouraged.

Details:

Preferred Student Year

First-year, Second-Year, Junior, Senior

Volunteer

Yes

Yes indicates that faculty are open to volunteers.

Paid

Yes

Yes indicates that faculty are open to paying students they engage in their research, regardless of their work-study eligibility.

Work Study

No

Yes indicates that faculty are open to hiring work-study-eligible students.

Researcher


Assistant Professor of Informatics in Biostatistics and Epidemiology