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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two
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contact Enrico Glaab : Your profile We seek a bioinformatician or computational biologist who is well versed in the machine learning and statistical analysis of biomedical data, the use of artificial
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/recruitment/2-year-postdoctoral-p… ** Project ** Computational and high field MRI characterization of learning and decision-making ** Supervisor and contact ** Dr Florent MEYNIEL https://www.unicog.org/lab
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Eligibility criteria The recruited person must have expertise in cosmology, numerical development and machine learning. They must be proficient in the Python programming language, with experience in JAX being a
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individuals perform example gestures while demonstrating the desired sound output. The system then learns and generalises these associations, allowing personalised and adaptive control over real-time audio
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example gestures while demonstrating the desired sound output. The system then learns and generalises these associations, allowing personalised and adaptive control over real-time audio generation
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and economy that respect people and their environment. We are looking for our next postdoctoral researcher in computer graphics and machine learning to join the Image, Data and Signal (IDS) department
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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Epidemiology of Malaria), led by Aimee Taylor. Using simulation-based inference (SBI) with deep learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum