Kimberly Querrey Fellowship in Data Science

The application of artificial intelligence and machine learning is central to the future of biomedicine. The Kimberly Querrey Fellowship in Data Science is designed to support the training and career development of exceptional MD or PhD graduates on their path to becoming successful academic leaders. The Kimberly Querrey Fellowship provides a generous stipend and resources to support a postdoctoral fellow for a period of 1-3 years as they develop the skills, publication track record, and funding necessary to become a leader in academic medicine. This support provides Fellows with the autonomy to devote all of their time to building a strong research program.

The Kimberly Querrey Fellow in Data Science will leverage the wealth of clinical and molecular data generated by investigators in the Simpson Querrey Lung Institute for Translational Sciences (SQLIFTS) from patients with lung disease. Kimberly Querrey Fellows in Data Science use these data to develop and validate novel machine learning and artificial intelligence tools to understand disease pathobiology that will guide drug discovery. The Fellow will receive dedicated mentorship within an individual laboratory in the Institute. They will work one or more mentors, often supported by large collaborative grant awards, to develop an independent program of research. The Fellow will benefit from intensive mentorship and support for their academic development through SQLIFTS.

Fellows take advantage of the rich intellectual environment and the state-of-the-art research facilities within SQLIFTs and at Northwestern University and of the high-quality, high-volume clinical programs in the Canning Thoracic Institute at Northwestern Medicine.

To Apply

Applicants must include the following:

1. A one-page personal statement outlining accomplishments and career goals
2. CV
3. Three letters of recommendation.

The application deadline is September 15, 2025. Please submit your application here.