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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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details of 2-3 references to laura.cantini@pasteur.fr For more information : https://research.pasteur.fr/en/team/machine-learning-for-integrative-genomics/
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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 1 day ago
Methods and Programs in Biomedicine Update, 2024, 5:100148. https://doi.org/10.1016/j.cmpbup.2024.100148 de Hond, A.A.H., Leeuwenberg, A.M., Hooft, L. et al. Guidelines and quality criteria for artificial
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programming task within the thematic context of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bi-molecular-machine-learning/ Employment conditions This is a
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 6 days ago
will develop computer vision, machine learning and control algorithms for a robot to perform packaging tasks. Human demonstrations will be used to generate data for learning. These data will encompass
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Summary We are seeking an undergraduate student to assist with data preprocessing and machine learning tasks. Career Readiness Competencies: Communication Professionalism Teamwork Essential
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, learn and grow. Join us and contribute to our culture. Additional Information: Purdue’s benefits summary https://www.purdue.edu/hr/Benefits/ Purdue will not sponsor employment authorization
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candidates should review the application requirements, learn more about IU and The Luddy School, and apply online at: https://indiana.peopleadmin.com/postings/31722 Salary will be commensurate with education
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(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical