hiring a postdoc in AI/ML for Social Good

[Daniel Neill]

Dear friends and colleagues, I am delighted to share that my Machine Learning for Good Laboratory (at NYU Courant Institute, Department of Computer Science), is planning to hire a postdoctoral associate in the general area of AI and machine learning for social good, jointly with my NYU colleague Emily Black. Please spread the word, and please share the position description with anyone who might be a good fit: https://apply.interfolio.com/193352

We are seeking candidates with demonstrated ability to create novel machine learning methodology supported by rigorous theory, who have the background to assist with our newly NIH-funded PRISM project ("Precision Prevention Strategies for Mental Health") and other projects jointly conducted between my lab and Emily's Impact-Driven Evaluation for AI (IDEA) lab. We are particularly looking for individuals with expertise in the following subareas of machine learning: causal inference, algorithmic fairness, and theoretical properties of large language models (e.g., stability, fairness, and model multiplicity). Experience in working with complex data (such as health and urban data) is a plus, as is a strong interest in applying methods to impactful public health problems.

Interested candidates should apply directly to the Interfolio link above. Thanks!

All the best,

Daniel

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Daniel B. Neill, Ph.D.

Professor of Computer Science, Public Service, and Urban Analytics

Director, Machine Learning for Good Laboratory

Courant Institute- Department of Computer Science / Wagner School of Public Service / Center for Urban Science & Progress

New York University

daniel...@nyu.edu

http://www.cs.nyu.edu/~neill

http://wp.nyu.edu/ml4good