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semester hours per week (2 SWS). Participation is expected in the EMOS program, the Munich School for Data Science (MUDS), and the Munich Center for Machine Learning (MCML). Cooperation with the institute’s
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In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits Forschungszentrum Jülich is one of the largest research centers in Europe, with
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, including gas turbines and combustion engines. We combine advanced computational fluid dynamics, theory, machine learning, high-performance computing, and experimental methods to investigate and model complex
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and is associated with the management of the Institute's own 500 m² clean room facilities (https://www.igm.uni-stuttgart.de/en/research/clean_room_lab/ ). We are looking for an individual with
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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials
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. To analyze and control thermoacoustic instabilities, we combine fluid mechanics, acoustics, and combustion with methods from control engineering, nonlinear dynamics, and data-driven modeling (machine learning
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modeling, and scientific machine learning to enable efficient simulations of complex molecular processes across realistic time and length scales. https://doi.org/10.48550/arXiv.2604.24245 https://doi.org
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with a strong background in mathematics, computer science, or machine learning. The work has a strong focus on developing new objectives or new architectures for medical deep learning and on new ways
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uncertainty, since misclassifications can lead to poor energy management decisions or inappropriate building automation responses. The goal of this project is to design and validate a machine learning framework
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
highly motivated AI Scientist (f/m/x) (best: Computational Pathologist / Machine Learning Scientist for Digital Pathology) to join our efforts in developing AI-driven virtual staining pipelines for cancer