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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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, or Python); Creating and managing very large datasets; Managing and mentoring research assistants (RAs); Machine learning skills; Writing papers for management and economics journals; Interest in reskilling
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research assistants (RAs); Machine learning skills; Writing papers for management and economics journals; Interest in reskilling initiatives; Working with partner organizations or companies. Basic
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of References Allowed Keywords statistics, biostatistics, computer science, economics, health care policy, causal inference, machine learning
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/guidelines . Minimum Number of References Required Maximum Number of References Allowed Keywords statistics, biostatistics, computer science, economics, health care policy, causal inference, machine learning
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, or Stata); · Creating and managing very large datasets; · Machine learning skills. Basic Qualifications A Ph.D. in any business discipline, organizational behavior, economics, statistics, environmental
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for analysis (e.g., text manipulation); · One or more computational environments for statistical analysis (e.g., MATLAB, R, or Stata); · Creating and managing very large datasets; · Machine
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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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protein coding genetic association data with functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits This position is