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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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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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. The current project deals with the use of machine learning / artificial intelligence and big data science in the field of synchrotron research. Development and application of machine learning / artificial
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. Job description: - first-principle modeling and simulations of electrolytes - development of new machine learning strategies and quantum simulation approaches - application of specially developed
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Neurobiologie (ZMNH) Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI (baiome.org) to complement our lively and enthusiastic team of machine learning and
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learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k – 57k
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learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k – 57k
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 8 days ago
. Helmut Grubmüller) is inviting applications for a PhD Student or Postdoc (f/m/d) for the project Theory and algorithms for structure determination from single molecule x-ray scattering images. Project
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vision, machine learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge