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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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do: Design, fabricate, characterize, and optimize electrochemical biosensing technologies for real-time detection. Develop and implement novel surface chemistries to improve sensor performance
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appointment). Strong background in statistical or machine learning methodology, optimization, or high-dimensional data analysis. Proficiency in R or Python; experience with deep learning, causal inference
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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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, Biostatistics, Computer Science, Statistical Genetics, or a related quantitative field (by the time of appointment). Strong background in statistical or machine learning methodology, optimization, or high
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and present results at peer-reviewed venues and conferences. Example project areas Performance analysis and optimization of end-to-end scientific workflows, including those originating at DOE facilities
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data Clear scientific writing and communication; a track record of publications Experience with causal inference Bonus: experience with explainable ML, optimization/decision strategies, or work with EHR