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conferences Your profile - Master?s degree in physics, mathematics, computer science, or a related field - strong analytical skills and solid theoretical background - experience in machine/?deep learning and
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position: Deep learning for phase-contrast synchrotron X-ray tomography Reference code: 2026
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skills (preferably Python) and experience with machine learning frameworks such as PyTorch or TensorFlow. Strong analytical and problem-solving skills and interest in mathematical research. Experience with
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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interfacial chemistry on the atomic-scale is as yet unresolved, owing to the lack of sufficiently suitable analytical capabilities. In this project, the PhD candidate (m/f/x) will employ atom probe tomography
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learning approaches. A central aspect of this project is the formation of a complex sorption layer—known as the eco-corona—on the nanoparticles and its influence on pollutant sorption. We are seeking to hire
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contract is based on § 2 WissZeitVG. Your Tasks: Generative diffusion models (DMs) learn to reverse a diffusion process from an analytically known prior distribution to a target distribution that is inferred
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will apply machine learning — in particular physics-constrained symbolic regression — to discover compact analytical spin-Hamiltonians and their parameter dependencies. These Hamiltonians will feed large
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in