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until filled. Required qualifications: The candidate must have a PhD in Quantum, Condensed Matter or Solid-State Physics (or related topics). References: [1] Universal control of a six-qubit quantum
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LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria •PhD in accelerator physics or a related discipline •Training or experience in accelerator physics
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Integration of microglia into assembloid systems and optimization of co-culture conditions Phenotypic characterization of disease-relevant features, including neuronal loss, microglial activation and astroglial
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partnership with the Charles Sadron Institute, - Contributing to the development of dedicated acquisition electronics, - Conducting tests on the developed devices, - Analyzing the obtained data, - Optimizing
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of suitable catalysts and the optimization of operating conditions. This project aims to investigate the catalytic conversion of phenolic monomers via the catalytic hydrogen transfer process in both gas and
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and optimization of metasurfaces exhibiting tailored spectral responses at selected near-infrared wavelengths • Development of angularly robust optical functionalities over wide ranges of incidence
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of chemically storing and releasing hydrogen, using methanol as a reservoir. Main activities: • Utilize global optimization codes and perform DFT calculations on supercomputers. • Analyze results and
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analytical skills and scientific rigor. 🇬🇧 You enjoy teamwork and possess excellent oral and written communication skills in English. 🎓 The successful candidate must hold a PhD in Computer Science, obtained
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and optimization of metasurfaces exhibiting tailored spectral responses at selected near-infrared wavelengths • Development of angularly robust optical functionalities over wide ranges of incidence
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benchmarking and comparative evaluation of gene perturbation models across diverse single-cell datasetsCollaborate closely with Helical-AI on scaling, optimization, and integration of the developed models within