127 computer-science-programming-languages-"CNPEM" positions at Nature Careers in France
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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Nature Careers | Port Saint Louis du Rhone, Provence Alpes Cote d Azur | France | about 15 hours ago
and and experience in computational methods applied to structural biology. A strong publication track record.
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of the group For more information, please contact professor J.S. Coron (jean-) or check the website www.crypto-uni.lu . Your profile Master's degree in computer science or mathematics Good programming skills
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The candidate should preferably have a PhD in Computer Science or Robotics with a solid background on deep learning and 3D scene understanding. Experience with LiDAR and Computer Vision is a plus. The candidate
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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning
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have a PhD in computer science, mathematics, physics, or related fields, with a passion for programming. A desire to contribute to the development of open-source software within the context of the agreed
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to identify existing drugs that may be repurposed for rare disease treatments, accelerating the development process by leveraging known drug safety profiles. -Structural Biology: Implementing computational
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nursing programs - Bachelors in the fields of surgery, anaesthesia/resuscitation, paediatrics, and mental health. A fifth program 'Bachelor of Nursing in General Care' will start in September 2024, while
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PhD degree in Computer Science, Physics or a related field Experience with parallel programming models Strong programming skills in C/C++ and/or Python Knowledge of distributed memory programming with
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, copyrighted, or biased. By studying brain data recordings and building computational models that mimic real populations of neurons, the project aims to uncover active unlearning: how the brain learns