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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 5 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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–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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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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foundations of medical deep learning. The project focuses on novel self-supervised objectives, information geometry, mitigating representation bias for rare pathological findings, and building next-generation
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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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via the Emmy Noether project “Stability and Solvability in Deep Learning”. This project focuses on mathematically analyzing machine learning algorithms with a particular focus on questions of stability
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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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-style models. Pretraining may use self-supervised, contrastive, masked-modelling, or generative objectives. Own research ideas are strongly encouraged. Your responsibilities • Develop deep learning
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strong interest in foundational research in the above-mentioned research areas strong programming skills, preferably in Python, including experience with deep learning frameworks (e.g., PyTorch, TensorFlow
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environment. Successful and rapid development and deployment of the technology will ensure EU's leadership in the exploration and exploitation of deep space, the next commercial space frontier. The program is