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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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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 1 day ago
communication, sociable with an appetite for working in a group. Additional skills appreciated: rigorous, organized, curious, autonomous, proactive and dynamic. A specialization in optimization, machine learning
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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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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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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/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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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape a new research program at the intersection
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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