56 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD scholarships at Forschungszentrum Jülich in Germany
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electrical engineering, computational engineering, or a related discipline A strong foundation in power system modelling and simulation Solid programming skills (Python, C++, or comparable languages) Interest
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: Masters degree in electrical/electronic engineering, computer engineering, computer science, physics, or related fields Experience with emerging memory devices A strong electronics background, including
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international research contexts Your Profile: Excellent Master’s degree in mechanical engineering, energy systems, computational engineering, or a related field Strong background in numerical methods and applied
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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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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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with chemists, engineers, and data scientists will enable the creation of a robust, high-throughput framework for future catalyst and layer development and efficient optimisation. The following topics
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and individually, for example through training opportunities and the structured JuDocS program for doctoral candidates: https://www.fz-juelich.de/en/judocs In addition to exciting tasks and a
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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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interdisciplinary and exciting field of neuromorphic and brain-inspired computing, collaborating with physicists, neuroscientists, materials scientists, and engineers FLEXIBILITY: Flexible working arrangements
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-ceramic joining materials, with a focus on interactions during the joining process and under operating conditions Optimisation of experiments, measurement methods and measurement technology, including