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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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/Administrative Internal Number: 495872 Department: Pharmacological & Pharmaceutic Salary: Commensurate with Experience/Education Description: Possesses, understands, and applies a comprehensive knowledge in area
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to advancing the understanding of the role of extracellular vesicles in the immune system, but also to apply the knowledge in clinical collaborations. Division The work will be performed at the Division
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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forms of knowledge production. It supports experimental research infrastructures that respond to these transitions across disciplinary and methodological boundaries. Within this framework, the Chair hosts
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research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we live in
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-angers.fr/poste/l3n5xsoefq-post-doctorante-en-machine-… Requirements Research FieldMathematicsEducation LevelPhD or equivalent Skills/Qualifications Knowledge: • The candidate must have a basic understanding
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management. Exchanges information with other departments or external contacts to perform role and achieve objectives. May coordinate own work with that of other work groups. Knowledge, Skills, and Abilities
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persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge
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determinants of health. The focus of this role is on cognitive decline and dementia, with an emphasis on: Applying epidemiologic, econometric, and other methods to strengthen causal inference Working with