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publishing in peer-reviewed scientific journals Your Profile Master’s degree in electrical engineering, physics, computer science, or a related field Strong academic background in embedded AI and in the
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electrical/electronic engineering, computer engineering, computer science, physics, or related fields Experience with emerging memory devices A strong electronics background, including experience in
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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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: Master's (M2) or engineering-school student in machine learning, applied mathematics or computer science Strong linear algebra; probability and optimization are a plus Solid Python and PyTorch Care in
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qualifications master student or equivalent (2nd/3rd engineering school year) in computer science and/or machine learning; some knowledge of the Python programming language; ability to work in a team
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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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, applied mathematics, computer science, computational engineering or a related discipline Sound knowledge of mathematical optimisation, control engineering or energy-management methods Experience in
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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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A recognized work-life balance environment A diversity and inclusion policy Corporate catering Applicant Profile With a background in computer science and AI or electronics, you are a problem solver
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Physics, Applied Mathematics, or Computer Science, with experience in deep generative models (VAE, diffusion) and Python/PyTorch. Applications from statistical physicists are welcome. STILL HESITATING