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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
Area of research: Scientific / postdoctoral posts Starting date: 01.07.2025 Job description: Postdoc (f/m/d): Machine Learning for Materials Modeling With cutting-edge research in the fields
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of machine learning and health sciences, with unique access to experimental and clinical data. Embedded in Munich’s thriving AI landscape, fellows benefit from world-class facilities, interdisciplinary
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of climate model output by means of classical statistical and machine-learning methods #coordination of scientific workflows among project partners Your profile #Master's degree and PhD degree in meteorology
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supported by an external team of deep-learning experts. You will also become an integral part of the Multiscale Cloud Physics Group currently being established by Dr Franziska Glassmeier at the Max Planck
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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
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your technical goals. Collaboration opportunities with the Nanoscale Science Department and the European industry leaders in electron microscopy and machine learning, as well as financial support to
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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talents and passion as we work together to drive forward scientific progress. The Institute of Machine Learning in Biomedical Imaging (IML) focuses on pioneering research to harness the power of machine
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Postdoc (f/m/d) Methods for Geochemical Exploration and Sampling Strategy / Completed PhD in the ...
# Work in an interdisciplinary team to develop analytical and statistical/machine learning methods for surface geochemical exploration # Preparation of multi-method exploration-campaigns for known deposits