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testing (e.g. cell culture and organoid models). As part of a third-party grant from the Federal Ministry of Education and Research, the BfR is working in collaboration with the University of Veterinary
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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The Chair of Non-Destructive Testing (www.zfp.tum.de) is devoted to research and teaching in the field of material characterization using non-destructive testing methods. The focus of the chair includes
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The INM – Leibniz Institute for New Materials in Saarbrücken, Germany, is an internationally leading center for materials research, a scientific partner to national and international research
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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mineral and metal-bearing raw materials more efficiently and to recycle them in an environmentally friendly way. The Department of Modelling and Evaluation is looking for a PhD Student (f/m/d) to work in
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highly motivated candidate to develop models integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing
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Your Profile: An excellent master’s degree with strong background in nano science, materials science, chemistry, chemical engineering, physics or related Experience with modeling of reaction kinetics
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of modern physical chemistry, materials science, and biochemistry questions. Our qualification program, measures for recruiting, gender equality and family friendliness are equally innovative and
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that span a broad range of modern physical chemistry, materials science, and biochemistry questions. Our qualification program, measures for recruiting, gender equality and family friendliness are equally