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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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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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in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien
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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 hours 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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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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. The primary objective is to design robust and efficient planning solutions—integrated within a digital twin—that account for the uncertainties and variability inherent in industrial processes. Machine learning
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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity