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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning
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theoretical and/or computational research in Nonequilibrium Statistical Physics and Active Matter, under the supervision of Ramin Golestanian. For more information concerning our current areas of research
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will engage in theoretical and/or computational research in Nonequilibrium Statistical Physics and Active Matter, under the supervision of Ramin Golestanian. For more information concerning our current
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. The topics are not limited. Information about the available topics and supervisors can be found under the following link: http://scads.ai/positions2025. The location of work (Dresden or Leipzig) depends
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position (contract-based) and one PhD fellowship in Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys). The PhD position is focused on efficient algorithms
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, template programming, and multithreaded development Experience with statistical computing environments such as R or MATLAB is essential Knowledge of Monte Carlo simulation methods using the Geant4 framework
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modeling and computational workflows Knowledge about machine learning: statistics and deep learning Experience in data analysis, visualization and presentation Good programming skills in languages such as
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., (2025) Molecular Plant. Reference: https://www.sciencedirect.com/science/article/pii/S1674205225000280 Tasks include cloning and construct creation experimental design plant growth and survival assays in
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scientific questions Proficient in scientific software (e.g., Gatan DigitalMicrograph, Python, Origin, Matlab, SRIM/TRIM) Basic knowledge of scientific data analysis and statistical evaluation Good command
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of Econometrics and Statistics, esp. in the Transport Sector and co-supervised by Prof. Dr. Klaus Bogenberger, Chair of Traffic Engineering and Control, TU Munich. Requirements: Excellent, very good or good