121 computer-science-intern "https:" "https:" "https:" "https:" positions at Forschungszentrum Jülich
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Profile: You are enrolled in a master`s programme in chemistry, physics, materials science or a comparable field of study and are currently planning to write your master`s thesis. Good prior knowledge
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other research groups, in particular at INW Business trips to synchrotron facilities Participation in international conferences (including presenting your research results) Preparation of scientific
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: INTERDISCIPLINARY TRAINING: An interdisciplinary training program, including academic research, international mobility, and industrial immersion INTERNATIONAL COLLABORATION: Collaboration with 32 international
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
reactor design and efficient heat integration Collaboration with the department experimental technology testing for the implementation of processes at laboratory, miniplant, pilot, and demonstration scale
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date (mobility rules of the Marie Skłodowska-Curie program) Masters degree in electrical/electronic engineering, computer engineering, computer science, physics, or related fields Coursework in
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. Your Profile: A Masters degree with a strong academic background in physics, mathematics, computer science, computational neuroscience, or a related field Excellent quantitative and analytical skills
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal
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(or equivalent) in computer science, applied mathematics, physics, engineering, biology, plant and agrosphere sciences, or another relevant natural science; Strong background in Structural Bioinformatics and
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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional