29 computer-science-intern-"https:"-"https:"-"https:" uni jobs at Nature Careers in France
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research axes , as well as research programs in computational biology, addressing the challenges of biological process modeling and multi-scale data integration. Successful applicants are expected to secure
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, combining physics, mathematics and computational and systems biology with classical biology to explore a wide range of research fields including microbiology, RNA, chromatin and chromosome Biology, cell and
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background in cybersecurity or computer science; experience in quantum communication and QKD would be a strong asset. Strong project management expertise in technical environments, covering planning, risk and
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the expertise of Dr. Torsten Bohn in nutrition and health and food chemistry, and Dr. Farhad Vahid in nutrition sciences and nutritional epidemiology. Key Accountabilities Carry out research experiments
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About the FSTM The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Faculty of Science, Technology and Medicine
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, education, and innovation. As part of the international Pasteur Network, the Institut Pasteur fosters collaborations that enhance scientific excellence worldwide. The Technology Department The Technology
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, demonstrated by publications in international, peer-reviewed journals and/or conferences Track record of innovative research in the design and/or use of AI, data science and/or computational approaches Strong
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INT-26028 INTERNSHIP IN ORGANOMETALLIC CHEMISTRY FOCUSED ON DESIGNING NOVEL CATALYSTS FOR ADDITIV...
and entrepreneurship in all areas. Apply online https://www.list.lu/en/jobs/interns/ Your application must include a motivation letter oriented towards the position and detailing your experience
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About the LCSB The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Luxembourg Centre for Systems Biomedicine
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on Intelligent Vehicles, vol. 1, no. 1, pp. 33–55, 2016. [2] M. Cerezo, G. Verdon, H.-Y. Huang, L. Cincio, and P. J. Coles, “Challenges and opportunities in quantum machine learning,” Nature Computational Science