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Field
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Master’s theses Requirements: Master’s or PhD degree with above-average results in Applied Maths (analysis, numerics, modeling) or in a comparable program with a strong math. focus and knowledge in
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and the implementation of modeling and experimental frameworks for additive manufacturing systems. Research activities will emphasize solid-state and fusion-based additive manufacturing (AM) processes
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 9 hours ago
HPC codes # Own research focus on one of the areas of # Parallel programming models or programming abstraction # parallel algorithms # performance/scalability analysis and optimization or # exploration
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Infrastructure? No Offer Description The selected candidate will lead the metabolic modeling efforts within our Biotechnology pillar. The primary goal is to use computational modeling and network analysis
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. Job Description: Two postdoctoral researcher positions are available in the laboratory of Dr. Sarah Kim (https://pharmacy.ufl.edu/profile/kim-sarah/) to apply modeling and simulation approaches
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physics, chemistry, biomedical engineering, or a related field. Candidates with experience in MRI/NMR, numerical simulations, and quantitative modelling are preferred. Experience with quantum sensing
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The post holder will join the Physical Oceanography and Palaeoclimate groups in the Department of Earth Sciences and perform numerical model data analysis relevant to two projects: MEZCAL and
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system design/modelling would also be an advantage. 7. The successful candidate will be fluent in both written and spoken English The primary duties for the post will include numerical modelling
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models Foundation models represent a breakthrough in AI, as did the shift from traditional machine learning to deep learning. Numerous models become available in the field of Earth Observation and can be
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scale. Key activities include: • Fracture mechanics and fatigue for bio-based composites • Numerical implementation and optimization. • Model calibration and validation. • Prototype deployment and testing