178 machine-learning-phd Fellowship positions at Harvard University in Ireland-University-Ranking-2024
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Details Title Postdoctoral Fellowships in Networking Support for Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science Position
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Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A
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Details Title Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI School Harvard T.H. Chan School of Public Health Department/Area Biostatistics Position Description
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Successful candidates will have publications in information theory and machine learning venues, such as IEEE Transactions on Information Theory, ISIT, NeurIPS, ICML, ICLR, and ACM FAccT. Experience in machine
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Details Title Postdoctoral Fellowship in Differentially Private Learning and Replicability School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer
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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals
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Human Frontier Science Program (HSFP): Postdoctoral Fellowships Eligibility: A research doctorate (PhD) or a doctoral-level degree comparable to a PhD with equivalent experience in basic research
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals
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analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional team members to develop hypotheses, interpret data, and