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-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape a new research program at the intersection
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. Development and integration of state-of-the-art machine learning techniques in the analysis and event reconstruction will be a major component of this work. - Characterization of silicon detection modules using
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the equipment, including the annual budget and the personal computer provided by the MARBEC laboratory for modelling and mapping work. - main mission: The researcher’s main role will be to model and integrate
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equipped with a range of sample environments, including a Langmuir trough and a reactor for chemical vapour deposition (CVD) growth of 2D materials on liquid metal catalysts (LMCat). Current in-house
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, accessible by bicycle and benefiting from a car-sharing scheme under a mobility agreement with the Montpellier metropolitan authority. Website for additional job details https://emploi-recrutement.ird.fr/offre
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to generate, under mild conditions and with unprecedented efficiency, chlorine atoms by monoelectronic oxidation of chloride ions. Votre mission You will be in charge of the methodological development of a
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spectroscopy, ionic conductivity measurements, NMR. - Excellent laboratory skills, with a strong commitment to laboratory safety regulations. - Excellent written and verbal communication skills in English
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. This project aims to evaluate its potential as a regulator of the antitumor immune response. The site is accessible by tram (Line A, Campus Illkirch station) from the Strasbourg train station or by car (parking
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’ team, led by Dr Hubert Schaller, as well as the Strasbourg Botanical Garden, where Frédéric Tournay is in charge of the collections. Where to apply Website https://www.unistra.fr/fr/recrutement
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong