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FieldComputer science » OtherEducation LevelPhD or equivalent Skills/Qualifications CANDIDATE ’S PROFILE The candidate should possess a PhD in machine learning or computer vision and have a strong publication
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perform compound screening, among other strategies. If this sounds like a good fit for you, send an email to manuela.garcia@uam.es and visit our websites to learn more about our work: 🌐 NeuroProtection
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Leonardo. The successful candidate will play a crucial role in developing and optimizing machine learning workflows for large-scale environmental data analysis, contributing to the creation of robust and
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skills. - Creativity in problem solving. Ability and eagerness to learn new skills outside own discipline. Work Program / Duties / Responsibilities: The research will be carried out in the framework
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engineers. Good written and spoken English. High self-motivation, autonomy, and strong problem-solving skills Willingness to learn as this is a very non-traditional project WHAT WE OFFER A 3-year postdoctoral
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Biology, Physiology and Immunology at the Faculty of Biology. Learn more about our research: https://www.ciberned.es/grupos/grupo-de-investigacion?id=28735 https://www.neurociencies.ub.edu/research-group
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Postdoctoral researcher in marine ecosystems modelling for the Marine and Continental Waters Program
of machine learning and AI algorithms and methods. Knowledge of species distribution models. Catalan and Spanish are valued LanguagesENGLISHLevelGood Research FieldOtherYears of Research Experience1 - 4
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, required to adequately incorporate molecular data, and model regulations of inflammatory and degenerative processes. Available datasets at the molecular level will be incorporated through machine learning
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spectrometry methods (including HRMS); in data management software. Ability to work independently and as a member of a team; Must be creative, flexible and eager to learn and expand their scientific network
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Experience in machine learning techniques Postdoc 3: Experience in the computation and analysis of hydrodynamic cosmological simulations of galaxy formation and evolution Experience in simulations