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Causal Inference Postdoctoral Scholar

The Arnhold Institute seeks to reduce health inequities via innovative research and products. We have an opening for a causal inference postdoctoral scholar to combine machine learning and econometrics approaches to health data. The position will focus on the scholar's career development by developing and executing a rigorous research program and developing new collaborations across healthcare. We have access to very rich (and large) health datasets that can be a significant career development asset. While the program will depend on the candidate but we anticipate the position to require 50% research, 25% writing, 15% career development, and 10% travel.

Responsibilities

  • Contribute to a creative research program with a focus on causal inference, machine learning, and health.
  • Lead and co-lead the publication of interdisciplinary studies at the intersection of causal inference and health.
  • Work with domain experts to translate machine learning science into useful products.
  • Travel to present at conferences and events to bring exposure to our work.
  • Be an active community member to help grow the "causality in machine learning" community
  • Lead and co-lead grant proposal preparation to advance the state-of-the-art of data-driven scientific discovery.

Qualifications

  • The successful candidate must be intellectually flexible with a proven track record of interdisciplinary work. We look for candidates who continuously step outside their comfort zone and work well with others outside their domain of expertise.
  • Algorithmic experience with large-scale predictive and inferential models. This is not a theoretical position. 
  • Experience with experimental design and statistical analyses related to the generalizability of statistical models (e.g. reusable holdout).
  • Working experience with causal inference from observational data, demonstrated by publications and/or link to software
  • A Ph.D. in computer science, statistics, or applied mathematics.

To Apply...

Email the following documents to james.faghmous@mssm.edu with the title of the position in the email title (e.g. postdoctoral scholar, assistant professor, etc.)

  1. Share the link to the source code for one inference project on Github.
  2. Share what you deem your most important publication/report with a paragraph why you chose that paper.
  3. A 2-page CV.
  4. The names and contact information of two professional references.

About The Arnhold Institute for Global Health

Health equity is one of the greatest challenges of our times. We believe that access to quality healthcare for people and communities is a fundamental human right. The data science and product teams develop technologies to close the health inequity gap in the US and globally. Besides our mission, there are several reasons to consider joining us:

  • We are startup institute backed by a generous $25M gift from the Arnhold family
  • Your work will have the opportunity to be applied in NYC's largest healthcare system and potential impact the well-being of millions of people.
  • We have some of the most interesting health/healthcare datasets available.
  • We are a team of young and ambitious professionals from diverse cultures and backgrounds
  • The opportunity to build a transformative effort from the ground up and leave a legacy for those that will follow in your footsteps.

  • Access to world-class designers, system engineers, and health scientists to drive high-impact interdisciplinary work.

  • Travel to global settings to work with and get to know amazing collaborators and cultures.

  • We are located in the historic NY Academy of Medicine right next to Central Park on Fifth Avenue. Many of our team members conduct walking meetings in the Park!

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