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Field
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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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German Cancer Research Center in the Helmholtz Association (DKFZ) | Heidelberg, Baden W rttemberg | Germany | 2 months ago
throughout the Helmholtz Association. Within HI, the Applied Computer Vision Lab (ACVL) at DKFZ develops state-of-the-art methods for image analysis and machine learning, supports researchers in
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Learning commencing on April 1st, 2027. The Junior Professorship in "Probabilistic Methods in Machine Learning" is at the interface of applied mathematics, statistics, and computer science. It is dedicated
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in the laboratory Document and evaluate experimental and simulation results Develop and validate machine learning and deep learning algorithms for photonic sensing applications What you contribute
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31.07.2026, Academic staff We are seeking a researcher in Scientific Machine Learning (SciML) to join the project "Data science at scale" at the Technical University of Munich, Germany. Ideal
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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 2 months ago
for 4 years Software Developer / Computer Scientist (m/f/d) specialised in AI & Machine Learning, Ref. 421 to support the further development and commissioning of the Real-Time Control (RTC) system
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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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position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Postdoctoral Researcher - Machine Learning for Plant Regulatory Genomics
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of the Free University Berlin and other research institutions. The Digital Humanities team seeks to appoint a Student Assistant (m/f/d) with a focus on Machine Learning or Data Science, up to 19 hours per week
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numerical simulations and machine learning in order to better understand and characterize active matter systems. A possible direction is to use physics-informed machine learning techniques to connect