61 computer-science-intern "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD positions at Forschungszentrum Jülich
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testing process Your Profile: Excellent masters degree in physics, electrical engineering, mechatronics, process engineering or a similar field Strong interest in pursuing research on electrochemical
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grades in the field of mechanical engineering, material science, physics, computational science or similar, preferably with a specialization in the field of theory and/or simulation Strong understanding
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strong interest in foundational machine learning research and its application to real-world scientific problems. You should bring: A completed university degree (Master or equivalent) in computer science
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internationally renowned scientific groups Membership in the HiTEC Graduate School and the TPChange PhD program, providing additional scientific and professional training, international networking, and exchange
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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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. 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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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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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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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional