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machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
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discipline (computer science, neurosciences, biology, cognitive sciences) • Skills in perception psychology, neurosciences, machine learning, tracking technology and/or computer graphics as well as interest in
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elements distribution, crystallographic texture), mechanical properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning assisted
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Your Job: In this position, you will be an active part of our "Simulation and Data Lab Applied Machine Learning". Within national and European projects, you will drive the development of cutting
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localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy produced by PBF-LB. After identification of the most relevant parameters adopting a
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-harvesting complexes. The research will use a combination of quantum and molecular dynamics simulations, electronic structure calculations, and machine learning approaches. These are similar to earlier work
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expertise in developing and training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills and
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knowledge of machine learning (e.g., in the areas of object detection and identification, generative AI, etc.) Good written and spoken English skills (min. level B2) Good written and spoken German skills (min
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 3 months ago
diagnosis of dementia. This will enable specific therapy to be provided at an early stage. In the project, artificial intelligence / machine learning and new multimodal imaging methods are used to carry out
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Degree PhD Course location Kaiserslautern Teaching language English Languages Discussions are held in English (100%). Programme duration 8 semesters Beginning Only for doctoral programmes: any time