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quantum field theory Experience with programming languages, in particular C/C++/Python Experience with Linux and high-performance computing Willingness to contribute with talks to international
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degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field. Proven ability to work as part of a team and collaborate on projects. Strong coding skills for
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collaboration with energy system modelers Your Profile Completed master's degree in a STEM field; a degree in computer science, data science, or an AI-related discipline is preferred Strong interest in
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workspace learning,” in European Conference on Computer Vision, 2026. [3] A. Brazi, B. Meden, F. M. de Chamisso, S. Bourgeois, and V. Lepetit, “Corr2distrib: Making ambiguous correspondences an ally to
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of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and research, the FSTM seeks to generate and disseminate knowledge and train
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arrays. Applicant Profile You are a final-year Master’s or engineering student specializing in electrical engineering, microelectronics, applied physics or computer science. You are comfortable with
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program in electrical engineering, energy systems, computer science, data science, applied mathematics, industrial engineering, or a related field, and have demonstrated very good academic performance in
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Your Job You will participate in an international team in an EU-funded Doctoral Network project called MINDnet. The project consists of 15 Ph.D. students at 7 universities, one research center and
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environment Of great advantage are: Experiences in numerical modelling Basic knowledge of data assimilation Experiences on high performance computing (HPC) Knowledge of FORTRAN programming language Please
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computing Excellent programming skills (e.g., Python, C/C++, Julia, or MATLAB) Interest in quantum computing, quantum algorithms, and hybrid quantum–classical computing. Previous experience is considered