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analysis. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR3228-CATKNO-050/Default.aspx Work Location(s) Number of offers available1Company/InstituteLaboratoire national des champs
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for deviations from SM expectations. This effort requires a global analysis of the LHC data to fully exploit the information it provides about physics at the TeV scale and beyond and thus maximise the LHC physics
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, electronics, image and data analysis, chemistry, and biology. In this position, the successful candidate will work on the development of a novel three-dimensional single-molecule localization microscopy
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-layer techniques (preferred/an asset, intermediate level). Proficiency in Python for scripting, data analysis, and automation (advanced proficiency required). Website for additional job details https
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metastability processes under different operating conditions (dark, illumination, electrical bias); Spatial analysis of performance inhomogeneities and degradation mechanisms using optical and electrical mapping
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high-resolution microscopy • Mammalian cell culture and genetic manipulation • Molecular and biochemical assays • Quantitative analysis of intracellular trafficking dynamics The project will be carried
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training in nuclear physics and/or nuclear reactor physics. Strong programming skills (Python and/or C++) and data analysis skills are required. Proficiency in stochastic neutron transport simulation
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reactor physics. Strong programming skills (Python and/or C++) and data analysis skills are required. Proficiency in stochastic neutron transport simulation software such as MCNP, Serpent 2, OpenMC, Tripoli
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strategies. It specifically aims to develop, explore, and evaluate new statistical analysis and diagnostic methods using different data sources to improve estimates of population size, temporal trends in
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experimental techniques and/or data analysis Qualifications: • Ph.D. in Molecular Biology or Parasitology • Strong background in cell cycle biology and/or parasitology • Excellent problem-solving skills and