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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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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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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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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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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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Department of Molecular and Cellular Biology, Harvard University https://projects.iq.harvard.edu/bellonolab Explore molecular mechanisms underlying unique adaptations and behaviors. Fellows have freedom to ask
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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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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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limited to) population dynamics, hydrodynamics, elastic structures, active matter, and nonequilibrium statistical physics. Applicants should arrange for letters of recommendation from at least three
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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