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backgrounds in statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research
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Ability to collaborate within CAUSALab and beyond the research group Additional Information: Per university guidelines, postdoc appointments are considered to be on-campus, full-time positions. Per
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Ability to collaborate within CAUSALab and beyond the research group Additional Information: Per university guidelines, postdoc appointments are considered to be on-campus, full-time positions. Per
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candidates will have access to local computing facilities and will have the opportunity to interact and work with researchers in both the Harvard College Observatory ( HCO ) and the Smithsonian Astrophysical
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learning; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic
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that machine learning AI approaches will prevail as a generic computing paradigm, and will find an ever growing range of practical applications, many of which will have to do with various aspects of
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that machine learning AI approaches will prevail as a generic computing paradigm, and will find an ever growing range of practical applications, many of which will have to do with various aspects of
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School Postdoc Office and other Harvard University resources. Our Research We are currently looking for postdoctoral researchers who want to contribute to our mission by leading research projects in one or
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School Postdoc Office and other Harvard University resources. Our Research We are currently looking for postdoctoral researchers who want to contribute to our mission by leading research projects in one
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ensembles of diverse opponents.” Neural Computing and Applications (2025). https://doi.org/10.1007/s00521-024-10511-9 de Arruda, H. F., Gracia-Lázaro, C., Aleta, A. and Moreno, Y. “Collective