55 postdoctoral-image-processing-in-computer-science-"Prof" PhD positions at Forschungszentrum Jülich in Germany
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Your Job: We are offering a PhD position dedicated to the advancement of cryo-EM image analysis methods at the interface of Structural Biology and Electron Imaging at the Forschungszentrum Jülich
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tools and concepts. Supervise student projects and BSc/MSc theses. Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field. Strong
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of software tools and concepts. Supervise student projects and BSc/MSc theses. Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: Promotion Job description: Your Job: Join an interdisciplinary team that brings state-of-the-art AI
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: A completed university degree (Master’s or equivalent) with excellent grades in computer science, materials science, physics, or a related discipline Practical experience in data science, including
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on investigating the change in the catalysts surface under relevant process conditions using spectroscopic analysis methods. Your task will include: Application of established and novel methods for the preparation
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Your Job: At the Electrocatalysis department of Prof. Karl Mayrhofer, we offer a PhD position within the team Nanoanalysis of Electrochemical Processes. Lead by Dr. Andreas Hutzler, the team is
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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and develops a wide range of topics related to chemical hydrogen storage along the entire process chain. We place a particular emphasis on LOHC technology, addressing issues across different scales. Our
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equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep learning, or signal processing; familiarity with