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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
interested in recruiting faculty members who use and develop artificial intelligence methods and mechanistic mathematical models to address fundamental questions in biology. Examples of research topics include
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Independent research and publication activities in the field of mathematical optimization with focus on nonsmooth optimization, stochastic optimization, or optimal control of partial differential equations
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position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Staff Scientist / PostDoc – Machine Learning for Scientific Applications You
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-dependent uncertainty, convex optimization, and combinatorial optimization. The postdoctoral researcher will have the opportunity to develop new mathematical models, reformulation techniques, and algorithms
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Salt Lake City, UT Type of Recruitment External Posting Pay Rate Range $70,000 - $82,000 Close Date 11/19/2026 Priority Review Date (Note - Posting may close at any time) Job Summary The Postdoctoral
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The postdoctoral scholar will be expected to: Conduct original research in quantum machine learning and AI, quantum algorithms for optimization and scientific computing, hybrid quantum-classical computing
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technology management, or smart grids. Experience in development of mathematical meta-models, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Starting date: 06.08.2026 Job
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range of complex optimization problems. The ideal candidate holds a PhD in Operations Research, Computer Science, Applied Mathematics, or a related field, and has a strong background in mathematical
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for pricing complex derivatives and risk measurement, numerical optimization algorithms for portfolio optimization and calibration of financial models. We will focus on practical applications to real-world