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responsible to develop and test the new software in collaboration with experts of genomics at Joliot and of computer science at MdS. Your mission will include: Discussions and set-up of the physical models
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pool of leukemic cells in sanctuary lymphoid organs leading to transformation in high-grade lymphomas. 3) the elaboration of computational prediction tools of progression and new preclinical models
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on Neural Information Processing System [20] Anish Agarwal, Munther Dahleh, and Tuhin Sarkar, A marketplace for data: An algorithmic solution, in Proceedings of the 2019 ACM Conference on Economics and
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Master’s degree in Health Engineering is recommended. ➢ Proficiency in English is recommended. The desired profile combines scientific rigor, the ability to work independently, and team spirit within a
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ability to work in a cooperative, multi-cultural and multi-disciplinary environment. Dynamism, self-organization, autonomy and drive. Interest for computing biology (R programming, image analysis) will be
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advances in machine learning and data-intensive approaches facilitate the search for better or even global minima via evolutionary computations or reinforcement learning. Objectives. The main scientific
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/2023.12.26.573306 (2023). Lake, B. M., Salakhutdinov, R. & Tenenbaum, J. B. Human-level concept learning through probabilistic program induction. Science 350, 1332–1338 (2015). The successful intern should have a
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. Interest for computing biology (R programming, image analysis) will be an additional asset. Contact & applications: Applications should be sent to pierre.guermonprez@pasteur.fr ; julie.helft@inserm.fr
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on stochastic Riemannian optimization algorithms, these methods still suffer from limitations in computational complexity. The post-doctoral fellow will build upon this preliminary work to investigate
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this technology for capturing and processing the pulse of a city. In particular, in many applications, DAS suffers from the multi-source aliasing problem and low-frequency noise, especially in noisy environments