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Field
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Details Title Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems) School Harvard John A. Paulson School of Engineering
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experimental activities. This postdoctoral research project will focus on reinforcement learning methods for generating complex structures for generation of virus capsids and therapeutic proteins for gene
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The postdoctoral fellow will lead and co-lead projects that combine computational modeling, machine learning, and EEG to answer questions about scene understanding and neural representation. The fellow will work
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, Social Sciences , Biomedical Informatics , Causal Inference , Computational Social Science , Data Science and Information , Data Visualization , Deep Learning , High dimensional Data , Large Language
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Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated working experience
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cross encoder architectures and retrieval augmented generation. Strong programming skills in Python and deep learning frameworks, familiarity with MLOps practices, data governance for sensitive health
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School: Harvard Medical School Position Description: The Department of Health Care Policy at Harvard Medical School seeks an experienced postdoctoral fellow with a specialty in health services research
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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refractive-index imaging of complex samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue
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, and the ability to read related scientific papers on cancer combination therapy. It would also require expertise in relevant AI methodology, such as deep learning architectures for property prediction