96 computational-physics "https:" "https:" "https:" "https:" positions at Forschungszentrum Jülich
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Computer Science, Mathematics, Physics or a related field Knowledge in Neuromorphic Computing or Computational Neuroscience is a plus Experience in mathematical modelling Excellent programming skills and experience
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the application which project you are specifically interested in. Further details on the projects can be found here: https://www.fz-juelich.de/en/jcns/careers/fellowships/tasso-springer-fellowship-program Your
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particles, depending on its polarity, aromaticity, and concentration Localization of the aromatic molecule within the initial lipid membrane as well as in the target membrane after the fusion process
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Bayesian computational statistics, differentiable programming, and high-performance computing, the project aims to deliver robust, interpretable, and scalable methods for metabolic flux analysis. You will
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Master`s degree in crystallography, material science, physics, chemistry, or a related field You have an interest in scattering methods, solid-state materials and ideally also knowledge in the field
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, or machine learning Solid mathematical and physics background, distinct analytical skills Very good programming (Python, C++) and computer (Linux, Windows) skills Excellent cooperation and communication skills
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the HDS-LEE graduate school program. Supervise interns and student projects. Your Profile: Excellent Master’s degree in computer science, physics, or mathematics (or a related field), with a focus on
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Early Operations phases Present your research at international conferences and in peer-reviewed journals Your Profile: A Master’s degree in physics or a related field is required Strong background in
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publications and project reports Support in establishing the institute Your Profile: Master`s degree in physics, chemistry, materials science, chemical engineering, or a related discipline Extensive knowledge
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entropy or Kullback-Leibler divergence vs. measurement time Analysis and documentation of the results Your Profile: Excellent academic performance in a master’s program in electrical engineering, materials