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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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The SiMul team (https://cran-simul.github.io) at the University of Lorraine is offering a fully funded PhD position on the theoretical foundations of self-supervised learning, focusing
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patient clusters and digital phenotypes, leveraging machine learning approaches to identify individuals at high CV risk based on clinical and biochemical markers, immune markers, digital health data (e.g
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, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to collaborating with researchers from other disciplines. The successful candidate will
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of the project is to use machine-learning assisted molecular dynamics simulations incorporating quantum effects for the identification of new variant-specific drug targets which will be validated experimentally
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
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); willingness to learn advanced quantitative methods Good command of written and spoken English Enthusiasm and enjoyment for research and science, strong personal commitment We offer Multilingual and
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, longitudinal analyses, multilevel analyses); willingness to learn advanced quantitative methods Fluency in both written and spoken English, along with proficiency in either French or German. Knowledge
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learning new techniques and finding answers to problems. You want to take advantage of the opportunity to do your PhD in two different countries and learn from different cultures and expertise. Where
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strong interest in computer science (software development, machine learning techniques, etc.) is desirable. · Applicants must have a maximum of 3 years of research experience after the PhD. · Language