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Description The Berlin Mathematical School is the graduate school of the Cluster of Excellence MATH+ ( http://www.mathplus.de ) and a joint endeavor of the mathematics departments
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, scientific computation, probability, optimal control, ordinary, partial, and stochastic differential equations, and dynamical systems; and applications of mathematics to biology, finance, and industrial
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possibility for negotiation). In this post you are expected to: teach (in English) the course “Stochastische Besliskunde” (“Stochastic Operations Research”), consisting of one two-hour lecture per week together
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the fields of differential equations and/or stochastic processes, as well as computational approaches and/or statistical methods of data analysis. You can find more information about our research area and our
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the light of the experiments. - Stochastic simulation of a noisy dynamics associated with the ODE. - Reiteration and redesign of the experimental part. Related activities : Writing reports in form
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academic performance. Experience with stochastic methods, risk and reliability analysis, and data analysis. Programming experience in Python, MATLAB, C/C++, or a similar language. Strong analytical
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possible including algebra, analysis, combinatorics, control theory, dynamical systems, geometry, numerical analysis, probability, statistics, stochastic analysis/control, partial differential equations, set
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of conduct, and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity Basic Qualifications: Ph.D. in mathematics, engineering, data/computational science
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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responsibilities described above. Within the department, research areas include optimization, stochastics, statistics, machine learning, artificial intelligence, and analytics, with applications to healthcare