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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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: In decreasing priority order, experience in: • Model fitting and/or image reconstruction in astrophysics • Active Galactic Nuclei • Machine learning • Optical long baseline interferometry and data
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the relationship between the increase in atmospheric CO₂ concentration and its sequestration as carbonates, particularly influenced by microbial processes. It focuses on the formation of carbonate sludge in various
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objectives. For example, digital image processing tools, such as filtering or mathematical morphology, could be evaluated to extract structural elements of road edges from images. By combining spectral and/or
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machine learning tools. The postdoctoral fellow will contribute to various aspects of the project, such as: * developing new theoretical and numerical approaches for determining the thermodynamic and
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the molecular mechanism for magneto-sensing. In their recently funded HFSP project, our partners M. Kosloff (U Tel-Aviv, Isreal) and I. Schapiro (U Dortmund, Germany) make the hypothesis that opsin
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, computer science (medical image processing), medical physics. Computer skills: Python, C++ (ITK, RTK). Languages: English required, French optional. Website for additional job details https://emploi.cnrs.fr/Offres
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. This will be made on different Cu-FR4-Cu laminate test-structures with a FR4 thickness ranging between 35 to 100 μm. A preliminary assembly process optimization will be performed (e.g., temperature
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Skills/Qualifications Strong background in Operating Systems and Linux development Knowledge of memory management mechanisms and system-level programming Experience with Machine Learning models (design
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly