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FieldBiological sciences » BiologyYears of Research Experience1 - 4 Additional Information Benefits The team hosted by the Extremophiles and Large Molecular Assemblies Group (ELMA) benefits from the infrastructure
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Benefits The team hosted by the Extremophiles and Large Molecular Assemblies Group (ELMA) benefits from the infrastructure gathered at the IBS (https://www.ibs.fr/ ) and the expertise of neighbouring groups
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French National Research Institute for Agriculture, Food and Environment (INRAE) | Toulouse, Midi Pyrenees | France | 2 days ago
30 Mar 2026 Job Information Organisation/Company French National Research Institute for Agriculture, Food and Environment (INRAE) Department IHAP 1225 INRAE ENVT Research Field Medical sciences
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contributing to education, research, and clinical excellence. Our department provides imaging services across a large academic health system and regional referral network, with a strong commitment to innovation
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Intern to support the development, benchmarking, and large-scale profiling of 3D cancer models within our multidisciplinary team. The ideal candidate is enthusiastic about experimental work, data-driven
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data collection activities, ability and interest in working with large datasets, and interest in working with interdisciplinary teams of researchers. The expectation is that the scholar would help lead
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to detail and adhering to data processing standards. Consistency with processing of file entries. Work with Librarians and Staff to process large data files Discipline Specific Required Qualifications
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, Computer Science, Engineering and Genomics. Previous experience working with disease vector data is not essential and we encourage all applicants interested in large-scale data management, computational design and
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seeking a Computational Research Assistant to support a research project focused on evaluating how clinicians interpret continuous glucose monitoring (CGM) data and how these interpretations compare
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Register to other national health registries, providing an unprecedented, population-level life course perspective on the benefits and risks of hormonal contraceptives. By integrating big data and advanced