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Mathematics (PDEs, Operations Research, Optimisation including Optimal Control, Information Theory including Coding Theory, Cryptography, Quantum Computing, Financial and Actuarial Mathematics, Mathematical
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, and written communication skills evidenced by a publication record in the area of control theory, mathematical optimization, AI, or machine learning. Preferred Qualifications: Publication record in
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mathematical background in reinforcement learning and/or control (e.g., optimal control, decentralized control, and/or adaptive control) with a strong desire to make an impact on energy/power grids are preferred
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course objectives. Make optimal use of available technology to enhance instructional methods. Supplement and alter, where appropriate, lesson plans, assignments, tests, and materials. Maintain accurate
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areas in Mathematics and AI: Machine Learning, Statistical Learning, Optimization, Computational Modelling, etc . Candidates with strong research potential or established academic records in these areas
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California State University, Long Beach | Long Beach, California | United States | about 6 hours ago
Machine Learning, Mathematics Modeling, Artificial Intelligence, Data Science, High-Performance Computing, or Optimization Successful experience at the post-doctoral level or in industry, ideally including
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Pennsylvania State University, Department of Mathematics Position ID: PennState-POSTDOC3 [#28088, REQ_75427] Position Title: Position Type: Postdoctoral Position Location: University Park
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, knowledge and experience: - Fluency in written and oral English - In-depth scientific knowledge in: mathematical optimization (convex optimization, operations research, fixed-point algorithms,...), inverse
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/systems theory and optimization is desirable. Full details of how to apply can be found at the following link: https://www.sheffield.ac.uk/acse/research-degrees/applyphd Applicants can apply for a
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theory, modeling, and AI-assisted optimization activities within the consortium. Reporting and dissemination of the results. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail=1074