75 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "https:" "CNRS " scholarships at Forschungszentrum Jülich
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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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computational engineering, mathematics, computer science, physics, engineering or a related field Strong background in numerical methods and machine learning Proficiency in at least one programming language
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international conferences Supervise student theses Your Profile: Excellent Master`s degree with a strong academic background in computational engineering, mathematics, computer science, physics, engineering or a
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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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development of your personal strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via
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, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a
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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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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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of results through high-quality publications and open-source software contributions Your Profile: Master’s degree in chemical engineering, biotechnology, computational biophysics, bioinformatics, data science
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manufacturing in resource strategies and system models for evaluating long-term transformation paths Your Profile: Excellent master`s degree in engineering, materials science, industrial engineering, energy