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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien
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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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Learning within the Department of Education and Social Work at the University of Luxembourg. The person will be part of a team in the dynamic organisational context of a growing, globally connected research
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of the project is to exploit such data to develop generative models for aptamer design. The candidate is expected to have a strong background in machine learning and statistical physics, with a real interest for
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. Responsibilities will include: Developing expertise in audiological test batteries Data wrangling, cleaning, and feature engineering Applying and implementing statistical or machine learning methods, depending
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Postdoctoral position: Developing a human lymphoid organ-on-chip to evaluate candidate mRNA vaccines
immunology, with expertise in T cell/B cell interactions and/or vaccinology an expertise in advanced cytometry a strong motivation to learn organ-on-chip technologies a track record of publications in relevant
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and educational issues with the common goal of contributing to an inclusive, open and resourceful society. Your role The Postdoctoral researcher will be working in the Institute for Lifelong Learning
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interactions If you meet the required education and experience but don't tick every technical skill listed, we still encourage you to apply! We value motivation, and willingness to learn, and a passion for data