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learning and simulation-based inference for searches for dark matter (or other “invisible” new physics signals) at the Large Hadron Collider, with the support of competent and friendly colleagues in
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and application of methods for simulating magnetism, particularly atomistic and multiscale simulations. The successful candidate will have the opportunity to collaborate with leading experimental and
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dynamics simulations and machine learning methods to study the structure and electrochemistry of disordered materials are also encouraged to apply. The project primarily aims to understand the complex
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focuses on the development of GPU-accelerated, high-fidelity thermal runaway simulation models for lithium-ion battery cells, modules, packs, and complete battery systems. Thermal runaway is a chain
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numerical simulations to understand molecular mechanisms of epigenetic regulation by the Polycomb and Trithorax group proteins. Project description Chromosomal rearrangements of the human MLL1 gene
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) including a complete publication list, Certified copy of doctoral degree certificate or documentation when the doctoral degree is expected to be obtained, Verified copies of other diplomas, list of completed
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well as your experience in the areas mentioned above (max. two pages), Curriculum vitae with publication list, Verified copy of doctoral degree certificate or documentation that clarifies when the degree
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manufacturing systems that strengthen operational robustness, improve resource efficiency and raise the quality of decision-making. The research will investigate how simulation-based optimization, digital twins
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candidate. A CV that includes a list of publications. A copy of the doctoral degree certificate, and other certificates or grades you wish to be considered. Contact information for two references. Incomplete
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a justification of the applicant's relevance to obtaining the position. Descriptions of preliminary research ideas are welcome. (Maximum two A4 pages.) Copy of degree certificate, link to or copy