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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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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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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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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 9 hours ago
) in Geometric Deep Learning to join the Machine Learning and Artificial Intelligence (MLI) g roup to perform research in geometric deep learning for materials science. This research is part of
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FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Strong foundations in Machine Learning and Deep Learning Excellent Python programming skills Experience with PyTorch
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, especially in quantitative subjects • Strong Python skills and experience with deep learning frameworks, preferably PyTorch • Solid foundations in machine learning, statistics, linear algebra, and model
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, and related fields (e.g., Graph Machine Learning) Tasks: scientific research in at least one of the above-mentioned research areas collaboration in national and international research projects, possibly
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and experience with modern deep learning frameworks (e.g. PyTorch) Solid background in machine learning, ideally with experience in NLP, large language models, or sequence modeling Interest in clinical
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–2 years, total 3–4 years) on deep learning for medical imaging. This DFG-funded project focuses on developing deep learning methods for medical and scientific imaging. The Professorship for Machine
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looking for a PhD candidate to work on research at the intersection of machine learning, data privacy, and medical imaging. The position is part of a three-year research project that investigates how