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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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both on the sequence and structural level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and
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of cellular behavior to advance gene and cell therapies — including CAR-T cell therapy and muscle stem cell regeneration. The successful candidate will apply machine learning, statistical modeling, and single
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have experience with applications of machine learning and deep learning on medical image data that you have experience applying methods within generative artificial intelligence to medical images and
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. The PhD Fellow will be affiliated with the Computer Networks Research Group (ComNet) at the department. The proposed PhD project aims to advance the field of 6G vehicular networks by harnessing the AI
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. The following is considered important in the assessment: that you have experience with applications of machine learning and deep learning on medical image data that you have experience applying methods within
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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
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of References Allowed Keywords statistics, biostatistics, computer science, economics, health care policy, causal inference, machine learning
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geometry, and/or data science. Specific topics of focus include, but are not limited to, linear response, random and nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics
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nonprofits to use machine learning and data science to modernize the public sector. We are an interdisciplinary team of data scientists, social scientists, engineers, and lawyers who are passionate about