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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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-microfluidics (Thomas Pfohl, Physics Institute, University of Freiburg), bacterial ECM mechanobiology and biochemistry (Liraz Chai, Hebrew University of Jerusalem) and theoretical modeling (Vasily Zaburdaev Max
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) at Heidelberg University, the following position (75%) for up to 3 years is to be filled by 01.01.2026 PhD position (f/m/d) in Vector-Borne Disease Modelling The place of employment is Heidelberg, in the Climate
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17.10.2025, Wissenschaftliches Personal Are you passionate about generative AI and digital twins for intelligent mobility systems? Do you see potential in using large language models, vision
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the pyramids and creating digital object models with numerical simulations, for example, using Salvus software or similar. - Publication of research results and presentation of results at scientific conferences
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approaches (e.g., agile methods, model-based development, CI/CD pipelines) in concrete research projects. Publication of research results at national and international conferences. Assistance in preparing
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working time models and the possibility of mobile working, because creative and innovative ideas can arise anywhere. We also attach great importance to intensive induction training and an open and collegial
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latest technologies Flexible working hours, part-time models as well as home office A corporate culture of appreciation and promotion of equal opportunities Extensive training and continuing education
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evaluation of efficient training and reconstruction pipelines involving deep learning models Find required initial conditions for LWFA simulations which yield the reconstructed observed electron buch shapes
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dynamic research environment with first-class laboratory facilities near Berlin and Potsdam a pleasant and appreciative working atmosphere flexible and family-friendly working time model and the possibility