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of Computation Group, seeks applicants for a postdoctoral fellowship to conduct research in differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic
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: https://www.nathlab.org As a successful candidate, you will: Collaborate closely with experimental scientists, mathematicians, and medical oncologists/surgeons to plan, design, and execute computational
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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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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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(http://vanallenlab.dana-farber.org/) to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts
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system transformation. Fellows will engage in rigorous empirical, computational, and theoretical research that integrates engineering models of power systems with modern econometric and economic analysis
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. - Contribute to the development of risk-prediction tools, biomarker panels, and precision-medicine algorithms. - Participate in NIH-funded translational studies involving spatial multi-omics, proteomics
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: https://faculty.medicine.iu.edu/relocation . The search will continue until the positions are filled. Basic Qualifications Required Qualifications: Ph.D. (by start date) in Computer Science, Biomedical
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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of QRI Fellow Mentors can be found here: https://quantum.umich.edu/fellows/ . Open to all quantum science and technology disciplines, including spectroscopy, photonics, devices, sensing, computation