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As part of its software suite provided to its clients, Cegid and its partners use cookies on this website to: Provide the basic functions of the website; Obtain audience insights; Allow users to use
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As part of its software suite provided to its clients, Cegid and its partners use cookies on this website to: Provide the basic functions of the website; Obtain audience insights; Allow users to use
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As part of its software suite provided to its clients, Cegid and its partners use cookies on this website to: Provide the basic functions of the website; Obtain audience insights; Allow users to use
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As part of its software suite provided to its clients, Cegid and its partners use cookies on this website to: Provide the basic functions of the website; Obtain audience insights; Allow users to use
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As part of its software suite provided to its clients, Cegid and its partners use cookies on this website to: Provide the basic functions of the website; Obtain audience insights; Allow users to use
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As part of its software suite provided to its clients, Cegid and its partners use cookies on this website to: Provide the basic functions of the website; Obtain audience insights; Allow users to use
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As part of its software suite provided to its clients, Cegid and its partners use cookies on this website to: Provide the basic functions of the website; Obtain audience insights; Allow users to use
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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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; PyTorch; parallel and GPU computing Applicant Profile The internship is intended for a final-year Master’s student or engineering student specialising in applied mathematics, signal processing or
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will initially focus on algorithm development and simulation. Starting from reference methods, you will evaluate different strategies and progressively incorporate realistic ReRAM device characteristics