175 parallel-computing-numerical-methods positions at Technical University of Munich in Germany
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knowledge of quantitative methods, particularly in statistics and econometrics; experience in machine learning is a plus Background in business/management/behavioral science Experience with programming
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: Completed master studies in the field of environmental sciences, forestry, landscape ecology, remote sensing or related fields Interested in remote sensing, quantitative methods and programming Prior
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numerical studies. Develop NanoLPC application in additive manufacturing by developing a multiscale simulation tool for keyhole dynamics and pore formation prediction suitable for PBF applications. Expected
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to the road? Then this position is just right for you! About us In the Autonomous Vehicle Lab, we develop the vehicle of the future with intelligent algorithms and methods. We are involved in numerous projects
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of the structure, dynamics and kinetics of these systems, we mainly use scattering methods and do experiments at large facilities. Time-resolved scattering experiments at large-scale facilities allow us to
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the possibility of an extension. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and
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for students. Requirements We require for the position the following: A Ph.D. in the field of Applied Mathematics, Computer Science, Computational Science and Engineering, or similar. Knowledge of numerics as
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its rich information content, conventional analysis methods have not yet fully realized its potential. This research project aims to develop a robust AI foundation model based on modern Transformer
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scientific work on design automation for quantum computers and develop methods and software tools dedicated to the design and realization of quantum algorithms/circuits. One of the main challenges in
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these materials into high-performance fibers and functional materials. By manipulating molecular interactions through chemical and physical methods, we tailor the structural and mechanical properties of bio-based