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dynamics, data science, and machine learning are beneficial. Please submit your detailed application with the usual documents by August 15, 2025 (stamped arrival date of the university central mail
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(master’s or equivalent) with excellent grades in the field of data science, material science, mechanical engineering, physics, or similar, with a strong machine learning or simulation background In-depth
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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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written and spoken English skills High degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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therefore teams up materialists, electrical engineers, and computer scientists of TUD, RWTH Aachen and Gesellschaft für Angewandte Mikro- und Optoelektronik mbH ( AMO ) in Aachen, Forschungszentrum Jülich