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. Previous experience in magnetism, spin dynamics, nanofabrication, electrical measurements, 2D materials, programming and machine learning would be advantageous. Candidates should also be able to work
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Thesis subjects A question ? Check our FAQ CEA vacancy search engine Keywords (e.g. Sales engineer Paris) Contract Category Job location Offers to our candidates CEA View all vacancies RSS and other
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technologies Polymer science & engineering, process systems engineering & modelling, chemical reaction engineering, fluid dynamics & microfluidics AI, machine learning & automation technologies for
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programming and applied mathematics, and interested in neural networks and their hardware implementation. Some experience in machine learning would be an asset. Prior knowledge of emerging memory
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EN FR Go back Scroll to top Share Research Engineer in Bioinformatics — EVUTERO Project Postdoc position in Machine Learning for Integrative Genomics © Institut Pasteur - Photo by Perrine Bomme, Lise
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doctoral programme in question, the following are considered as other qualifications: Strong foundations in Machine learning and reinformement learning. Cloud computing and cloud technology. Low-level
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automatisé - H/F Ref. : 2026-41487-S2091 Postdoc Post-doctorat - Interaction spin-réseau par simulations ab initio et Machine Learning - H/F Ref. : 2026-41507-S2111 Postdoc Essonne (91) Bruyères-le
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The Chinese University of Hong Kong, Shenzhen | Eastern Shores, KwaZulu-Natal | South Africa | 20 days ago
, Life Science , Mathematics , Physics Job Type Faculty Member , Principal Investigator , Professor Employment - Hours Full time Duration Fixed term Qualification PhD Sector Academia Apply now Save job
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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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Biological Sciences Division - The University of Chicago | Chicago, Illinois | United States | about 2 months ago
computation, organismal behavior and cognition, immune-microbiome interactions, and regeneration Machine-learning foundations for multimodal integration of data across genomics, metagenomics