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communications or conferences. During the contract period, the successful candidate will be part of the 'Social and Political Dynamics of Private Life' team at the CMW laboratory. The candidate must hold a PhD in
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Postdoctoral researcher in the analysis of single-cell and spatial transcriptomics experiments (M/F)
University of Strasbourg. The selected candidate will work at the IGBMC and benefit from an exceptional international scientific environment. The IGBMC has around 40 teams divided into four scientific
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• Develop, consolidate, and optimize fMRI and EEG neurofeedback algorithms. • Design, integrate, and test standalone neurofeedback software (software suites for clinical environments). • Contribute
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Impacts (IFAECI, IRL 3351 CNRS–IRD–CONICET–UBA) in Buenos Aires. IFAECI is an international research unit dedicated to climate–environment interactions in South America, bringing together the expertise
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. Applicants should hold a PhD degree in Earth sciences, atmospheric sciences, physics, or similar fields, with: (i) a background in dust processes and lifecycle; (ii) experience in computer programing (Python
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of these processes on the atmospheric lifecycle and fate of microplastics, including deposition to urban and remote environments. - Write and publish scientific papers describing the results. - Participate in project
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well as their electrical characterisation. His/her role will involve overseeing all nanofabrication activities within the project, including the development of new cleanroom processes, as well as training PhD students in
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FieldEngineeringEducation LevelPhD or equivalent Research FieldPsychological sciencesEducation LevelPhD or equivalent Research FieldNeurosciencesEducation LevelPhD or equivalent Skills/Qualifications PhD in psychology
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of the European project DIVE, which aims to develop a digital twin of the environment. In this project, France Energies Marines intends to implement a digital twin of the atmospheric environment of an offshore wind
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architectures capable of combining data from morphological MRI (T1, T2, FLAIR) and MRS (metabolic spectra) for better tumor characterization. 2. Design predictive models of tumor growth over time, integrating