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, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of coarse-grained models that can be analyzed and simulated
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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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algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software
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& Other Requirements Demonstrated abilities in mathematical modeling, analysis and/or scientific computation, scientific software and algorithm development, data analysis and inference, and image analysis
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, statistical physics, dynamics of stochastic processes, analysis and/or scientific computation, scientific software and algorithm development, data analysis and inference, and image analysis Ability to do
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challenge meeting this requirement is the simultaneous need for low-power consumption. The main objective of the project is to develop a complete end-to-end high-performance DNN system for on-premise
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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only within dense, highly interacting systems, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of
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The Position We are seeking an independent and motivated researcher for a Postdoctoral Fellowship in Aviv Regev’s lab to apply develop edge algorithms for analysis of single cell genomics profiles
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, and data analysis for human subjects research. · Develop and apply computational models and algorithms to support robotic augmentation studies. · Contribute to manuscript preparation and dissemination