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Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
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Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
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Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
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team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ . What you’ll do: Design, fabricate, characterize, and optimize
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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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characterization, and functional properties of milk proteins and peptides. Our primary research goal is to understand their impact on human health. Our current projects involve developing and optimizing methods
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of medicinal chemistry. The candidate will be responsible for designing, synthesizing, and optimizing molecules targeting GPCRs (cannabinoid receptors; allosteric and orthosteric) and ion channels (a4b2 nAChR
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record of or exceptional promise for research. The fellow will work with Prof. Sam Petti on developing methods for modeling, optimizing, and interpreting biological fitness landscapes. Successful
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tumors using high-throughput sequencing technologies. Develop, optimize, and manage bioinformatics pipelines for processing and analyzing large-scale sequencing data (e.g., whole exome sequencing, RNA
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the last three years. Solid experience with AI/machine learning methodologies, particularly those applicable to network optimization. Proven ability in programming and familiarity with network simulation