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implicated genes act in neurons and circuits. We use large scale, unbiased, systematic approaches in collaborative multidisciplinary research teams. This postdoctoral fellowship in the Arlotta lab involves
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to optimize cellular performance. The Fellow will develop an independent research project aligned with the broader goals of the collaboration and will have opportunities to lead publications, make scientific
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establishing and optimizing long-term molluscan cell culture systems and advancing next-generation in vitro models for fundamental and translational research. Position Description · Develop, optimize, and
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fellow to perform research on agentic AI, foundational modeling, optimization, and control of multiagent autonomous systems with an application in renewable energy and power grids, in addition to working
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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Together, these research directions seek to reimagine how buildings and cities operate—optimizing energy use, enhancing human well-being, and reducing carbon emissions at scale. We are seeking multiple
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Details Title Postdoctoral Fellow in Biomedical Informatics (Cai Lab) School Harvard Medical School Department/Area Biomedical Informatics Position Description A Postdoctoral Research Fellow
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of optimizing pipelines for large-scale genomic projects. Special Instructions Required documents: CV Research summary of PhD work. Cover letter describing your interest in the lab and initial ideas for new
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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