67 linked-data-"https:"-"https:"-"https:"-"https:"-"https:"-"Computer-Vision-Center" Postdoctoral positions in France
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-performance computing is an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific
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data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Postdoctoral Researcher in Computer Science Employer
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Your Job Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant applications, e.g
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the interface of machine learning and biology, developing innovative machine learning methods for single-cell data analysis (tools developed by the team: https://github.com/cantinilab). Single-cell
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successful candidate will be part of a collaborative research center (CRC1451), located at the University of Cologne, that brings together neuroscientists investigating genetic factors, cellular and synaptic
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data systems and research infrastructure. For further information, please contact Dr. Sandrine Medves (email address: ). Your profile Core qualifications: A PhD in computer science, medical informatics
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Alexander Skupin: Your profile Core qualifications: PhD in bioinformatics, computer science, computational biology, physics, data science, or related fields Strong interest in interdisciplinary and
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project will be realized in close cooperation between the JCNS at the Heinz-Maier Leibnitz Center in Garching and the JCNS institutes in Jülich and Aachen. The place of employment will be Aachen: Project
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Synthetic Data Simulation for Malaria Genomic Epidemiology Team: Infectious Disease Epidemiology and Analytics Department of: Global Health Member: Aimée Taylor Scientific Fields Diseases Organisms
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) and structural engineering performance in spent fuel Bridge the gap between theory and experiment by integrating microstructural and experimental data into computational models to validate predictive