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Field
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algorithm that interface with interpolated geotechnical fields to generate adaptive, variable-length stope geometries. Calibrate and validate the developed models using real-world mine data Develop, document
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automated analysis of nuclear cardiology data using novel algorithms and machine learning techniques, and on the development of integrated motion-corrected analysis of positron emission tomography (PET
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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are interested in research at the interface between geometry, mechanics, materials science, computation, and control theory. PhD positions Applicants for PhD positions are expected to have a strong background in
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approximations to solution of PDEs Information Geometry theories Monte Carlo Sampling methods. Candidates with strong background and track record in general computational and applied math or PDE analysis will also
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advanced vehicle concepts and better control systems. Actively changing the geometry of the aerodynamic lifting and control surfaces, enables reconfiguration of vehicle structure in real-time to optimized
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Systems Control Theory Formal Methods Reachability Analysis Computational Geometry Context The applicant will be directly advised by Prof. Matthias Althoff (https://www.ce.cit.tum.de/cps/members/prof-dr-ing