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seismologist with strong theoretical and computational skills to develop new probabilistic and physically informed approaches for seismic hazard assessment. The successful candidate will contribute to the next
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Position Location: Garching, Bayern 85748, Germany [map ] Subject Areas: Condensed Matter Physics / cond-mat-th , Condensed Matter Theory , Quantum Information , Strongly Correlated Materials , Theoretical
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Job Offer from September 18, 2025 The Max Planck Institute for Physics is engaged in fundamental research in particle and astroparticle physics from both experimental and theoretical perspectives
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qualifications: PhD or equivalent achievement (proof of independent research capability) in Machine Learning, Computer Science, Physics, Mathematics, or a related field Deep theoretical knowledge and extensive
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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | 2 months ago
Job Code: 403 Job Offer from October 02, 2025 The Max Planck Institute for Astronomy (MPIA) in Heidelberg plans to offer up to 10 postdoctoral positions for pursuing innovative theoretical
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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following areas: Mathematical Analysis/ Numerical Analysis/ Theoretical Machine Learning Please note: Applications from candidates with degrees in other disciplines (e.g., Computer Science, Engineering) will
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theoretical ecology, geosciences, applied mathematics, environmental physics, or a related field. Research experience in numerical modelling, preferably with knowledge of either eco-evolutionary models and/or
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guidance and support for employees, doctoral candidates and students Your Profile: Master`s degree with subsequent PhD in theoretical physics or a similar field Background and strong interest in developing
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agents in display-advertising auctions. The economic properties of such systems are still poorly understood. In general, learning procedures in game-theoretic problems can exhibit cyclic behavior or even