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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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depends on the background of a suitable candidate. The main topics of the group in the past few years were generative modeling, 3D reconstruction, image-editing, and deep learning using 3D data. More
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also have: (a) a proven record of academic writing in relevant fields; and (b) strong teamwork and collaboration skills. Preference will be given to those who have experience in developing deep
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immunity, or animal models of chronic inflammation Expertise in advanced immune phenotyping (e.g. spatial omics, single‑cell omics including deep learning, O-link proteomics, Crispr screening, human PBMC
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking a candidate with deep insight and interest in investigating the interaction between
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related to heart failure and cardiovascular biology. Develop and apply machine-learning and deep-learning approaches to identify disease-associated cardiomyocyte subtypes, cellular trajectories, and
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minimum qualifications at the time of hire. PhD in computer science, data science, or related discipline Track record of publications in Artificial Intelligence and Deep Learning in peer-reviewed
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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) years in Computer Science, Data Science, Computational Engineering, Bioinformatics, Computational Social Science, or another highly quantitative field with substantial emphasis on machine learning, deep
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aerial vehicle (UAV) imagery collection and processing, deep learning methods, and rangeland vegetation communities in Oregon and Idaho as part of an interdisciplinary team including researchers in plant