The Data Science Institute (DSI) at Columbia University is pleased to announce a new structure for its Postdoctoral Fellows Program, beginning with the upcoming cohort year.
For the first time, DSI postdoctoral fellows will be embedded within two of the Institute’s research centers, forming small, collaborative clusters that bring together scholars from across disciplines to advance data science research and its real-world applications.
Madiha Zahrah Choksi
Cornell Tech Human–computer interaction, privacy and security law, and policy community governanceWebsite
Christian Cianfarani
University of Chicago Trustworthy data science robustness, privacy, and statistical validity of machine learning systems Website
Nusrat Zahan
North Carolina State University Software supply chain security space Website | Google Scholar
Jenny Fu
Cornell UniversityAI-mediated communication toolsGithub
Raghav Singhal
New York UniversityDiffusion models, generative models, applications of machine learning in healthcareGithub
Poli Nemkova
University of North TexasModel reliability, uncertainty estimation, high-stakes decision support systemsWebsite
The DSI Postdoctoral Fellows Program supports exceptional early-career researchers whose work advances the frontiers of data science and its integration into other fields.
Beginning with the next cohort, the program will:
This new model reflects DSI’s commitment to embedding data science within domain research, creating environments where collaboration drives innovation.
The 2026-2028 Call for Applications has closed.
As a DSI Postdoctoral Fellow, you will:
Learning the Earth with Artificial Intelligence and Physics (LEAP) seeks fellows who will contribute to our mission of developing novel machine learning algorithms to harness data from high-fidelity simulations or sparse and noisy observations to improve climate projections. We are particularly interested in candidates who use physical and causal constraints or Bayesian approaches.
The Herbert and Florence Irving Institute for Cancer Dynamics seeks fellows who will support our shared mission of improving the understanding of cancer biology, origins, treatment, and prevention through data-driven approaches. We are particularly interested in candidates who will further advance core research in statistics, machine learning, AI and probabilistic modeling.
The Zuckerman Mind Brain Behavior Institute seeks fellows who are interested in using advanced data science and computational methods to understand how the brain works, from the neuron level to the cognitive level.
The Columbia Climate School seeks fellows who are interested in the interdisciplinary study of the science, consequences, and human dimensions of climate change. We are particularly interested in the urgent problems of Coastal Resilience, Global Decarbonization, Disaster Resilience, and Food for Humanity. We invite postdoctoral contributions in the basic and translational sciences, as well as in applied policy and direct societal interventions.
The Neuro Technology Center seeks fellows who will assist in our shared mission to support the development of advanced optical, electrical, and computational technologies for the study of complex neurobiological systems using data-driven methods. We are particularly interested in candidates who will further advance core research in computational neuroscience and its links with machine learning and artificial intelligence.
The Mailman School of Public Health seeks fellows who will assist in our shared mission to support and amplify health analytics. We are particularly interested in candidates who will further advance core research in the use of advanced data analytics to solve issues pertaining to population-scale health issues and preventive strategies, e.g., modeling climate effects on health, integrative-omics in large populations, impact of social networks on health, and data-streaming from personal monitoring devices.
The Center on Poverty and Social Policy seeks fellows who will support our shared mission to address the role of social policy in reducing poverty. We are particularly interested in candidates who will further advance core research in understanding trends in historical poverty, economic insecurity, immobility, and inequality, using novel data sources, and data-driven methods. Specifically we will further advance the usage of data that utilizes scanned receipts and optical recognition software to try to assess the impacts of the recently-enacted expansion of the Child Tax Credit on spending behavior.
The Department of Psychiatry seeks fellows interested in applying data science and cognitive systems to research on mental health, substance use disorders, and neuroscience. Opportunities for scalable data-driven science in psychiatry and clinical neuroscience are growing rapidly, and fellows would help advance the state-of-art in these areas. We are particularly interested in areas such as utilizing large and real-time medical record systems for addressing optimal patient-clinician feedback and treatment decisions; and utilizing multimodal neuroimaging data (including large consortia like the adolescent brain cognitive development [ABCD] study) for discovering underlying brain mechanism and development of psychiatric disorders.
The Department of Statistics seeks fellows who will support our shared mission of developing statistical insights into machine learning in the context of emerging challenges such as domain adaptation, representation learning, differential privacy, fairness, causal inference, etc. We are particularly interested in candidates who will expand core statistical methods and theory, as motivated by cutting-edge data science applications with broad societal impacts. Successful candidates are expected to engage and bridge between core faculty from Statistics, and faculty in any of the many departments involved with the Columbia data science center.