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compare population neural activity. The analysis of the network dynamics will build on principles of state space representation using statistical/machine learning and topological data analysis methods
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theoretical research, we combine nonlinear dynamics, statistical physics, and computational physics to understand physical mechanisms of biological function, and its robustness in the presence of noise and
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work: data cleaning, statistical data analysis, summarizing and writing research results. Other tasks may be included. The fellow will also be an active participant in the Harvard University research
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probability and statistics through the world-leading research activities of its Department of Actuarial Mathematics and Statistics, where the post holder will be located. Areas of particular strength include
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on sustainability measurement, as well on statistical methods and experience in working with standard business software (SPSS, Microsoft Office); independent and flexible working methods, willingness
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Strong mathematical skills (systems dynamic, probability and statistics, optimization theory) Excellent Matlab or Python programming skills Excellent written and oral English skills Personal
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Francisco Declaration on Research Assessment - DORA. Other qualifications Knowledge about the transport sector Programming skills Statistics Experience with traffic models and simulation Good written and oral
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following qualifications: Strong background in one or more of the following disciplines: artificial intelligence, computer science, machine learning, optimization, or statistics Strong applied mathematical
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structure and algorithm design; statistics; machine learning, deep learning and AI. Strong programming skills and experiences with popular data processing and machine/deep learning frameworks are essential
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at the interface between biology and mathematical sciences, and strives to apply cutting-edge theoretical and statistical frameworks to field data to resolve key questions in the context of both