DSI postdoctoral researchers are the next generation of leaders in data science.

Postdocs engage in independent and novel research in an environment that fosters multidisciplinary, collaborative work.

The Data Science Institute is actively seeking recent Ph.D. graduates and doctoral candidates that expect to receive their degree by July 1, 2023 who have explicit interests in advancing and/or applying data science to other domains.

Prior experience in data science is not required. We look for candidates with the courage and interest to learn a new field, to be part of a prestigious cohort of like-minded fellows with the goal of helping to define the field of data science into the future. 

Columbia University has a rich and diverse group of mentors whom our postdoctoral fellows collaborate. As part of the application process, you will identify potential mentors with whom you would like to work. Please find a list of DSI affiliated faculty members here; and see below for a list of collaborators that may be relevant to your application. 

Open Applications

Apply to 2023-2024 Postdoctoral Research Programs:

Data Science Institute Postdoctoral Research Scientist Application

Apply to Specialized Postdoctoral Research Positions:

Data Science Institute Data and Cancer Collaboratory Post-Doctoral Scientist

Postdoctoral Research Scientist (Powered by the Mastercard Center for Inclusive Growth)

Postdoctoral Research Scientist (Research Collaboration between Billinge Group and Toyota Research Institute)

Postdoctoral Research Scientist (Research Collaboration with the Natural Language Processing Group)

Application Process

Mentor Selection

  • Candidates should identify between two and five potential mentors who are current Columbia faculty members, including DSI faculty affiliates. Candidates are welcome to look beyond this list
  • If you are interested in applying data science to a specific domain, we encourage you to identify mentors from both a foundational area (applied mathematics, computer science, electrical engineering, machine learning, optimization, statistics, etc.) and a domain area. Using your input, the DSI will ensure the best possible match of mentor(s) for you

Dates and Deadlines

  • Application Deadline: December 15, 2022. Candidates are encouraged to apply as early as possible. There may be limited space for postdoctoral researchers beyond this deadline, and the DSI may consider applications from exceptional candidates. If you would like more information, please reach out to Ming Yuan, Associate Director for Academic Affairs.
  • Appointments Begin: July 1, 2023 (Cohort 5)


DSI Postdoctoral Fellows are guaranteed funding for two years through year-long renewable appointments. In addition to a competitive salary package, DSI Postdoctoral Fellows will also be provided with a research budget to be used for conference travel, computing equipment, and/or other research-related costs.

In collaboration with other schools, centers, and institutes at Columbia, the Data Science Institute also encourages candidates with specific interests in the following areas. Please indicate the area(s) within your cover letter.

Statement on Racial Equity

The Data Science Institute is committed to racial equity and justice. Research statements should explicitly state that the project will uphold these values, e.g., stating that the methods used to collect and analyze project data and the project outcomes reported are fair, just, and ethical.

Required Application Materials

  • A cover letter that explains your motivation for applying to this program and indicates your choice of mentors (and special interest area if applicable)
  • A curriculum vitae, including a list of publications
  • A brief research statement that summarizes current research interests, past accomplishments, and future research goals. It should contain a short proposal for the research activities you plan to do as a DSI Fellow, including a schedule with milestones, and statement and commitment to racial equity
  • Up to three representative research papers
  • Three letters of reference submitted directly by the recommenders

[Optional] A letter from a potential Columbia faculty mentor indicating an interest in your candidacy and your proposed research activities. This letter can be submitted directly to dsi-fellows@columbia.edu

Short List of Potential Columbia University Collaborations

We welcome applications for postdoctoral researchers interested in any of these collaborations. If you are interested in one of these opportunities, please note it in your cover letter.

  • 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.