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The Blacklow lab at Harvard Medical School invites individuals to apply for a postdoctoral fellow position investigating the molecular structure and function of transmembrane signaling proteins. Our
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Position Description The Bertoldi Group at Harvard SEAS is seeking a Post Doctoral Fellow in Mechanical Engineering. The ideal candidate will have research experience with kirigami structures and mechanical
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applications for research in structural biology of membrane proteins. Our lab investigates the structure, mechanism and evolution of several types of membrane proteins using biochemical, biophysical, and
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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applicants for a postdoctoral fellow position in the Brown lab at Harvard Medical School in Boston, Massachusetts. The Brown lab uses structural, biophysical, and biochemical approaches to decipher the biology
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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approaches in our lab and broader community across Harvard and collaborative interactions elsewhere. Candidates should have a strong background in cell biology, physiology, biochemistry, structure, and/or
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of electrophysiological data, work closely with medicinal chemists to use structure-activity data to design new compounds, apply for fellowship funding, contribute to the writing of grants and manuscripts, participate in
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research that integrates engineering models of power systems with modern econometric and economic analysis. Responsibilities include conceptualizing and implementing statistical and structural models
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. Responsibilities include conceptualizing and implementing statistical and structural models, developing scalable algorithms for system optimization and control, conducting policy-relevant economic analysis