124 parallel-processing-bioinformatics "https:" Fellowship positions at Harvard University in United States
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Description The Teamcore Group (https://teamcore.seas.harvard.edu) at the John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University seeks postdoctoral fellows to work on AI
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 06-Mar-26 Location: Cambridge, Massachusetts Categories: Academic/Faculty Computer/Information Sciences Internal
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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
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computational (bioinformatics) tools on human and mouse tissues and using in vitro methods on human cells, to explore the consequences of genetics variants on human biology. This is a multi-year position
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data analysis, contributing to research dissemination, and mentoring lab members along the way. With a combination of wet lab techniques and cutting-edge bioinformatics tools, you’ll explore novel
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discovery to find novel compounds to treat pain, epilepsy, and multiple sclerosis by modulating the function of particular ion channels. The work will be based on electrophysiological studies of ion channels
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with bioinformatic pipelines and approaches for working with methylation data, or a willingness/ability to learn these methods. The appointment is for one year with possibility of renewal based
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scientists, engineers, and/or doctors! The lab is committed to fostering lifelong learners in an environment that is diverse, inclusive and respectful. Learn more about our lab here: https
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development. More information about the lab and specific research areas can be found at https://sites.harvard.edu/zheng/. We welcome applications from recent chemistry or chemical biology PhD graduates with
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decarbonization, grid modernization, and the integration of distributed and flexible energy resources. Research topics may include—but are not limited to—AI-based grid operation and planning, reinforcement learning