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Field
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Research. Its’ one goal is to improve the health of all by advancing knowledge of life and disease, innovation in treatment, and public health research. The EpiAgeing team where the PhD candidate will be
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of Research ExperienceNone Additional Information Eligibility criteria In addition to a PhD in astrophysics, the candidates must have a solid background in stellar spectropolarimetry and / or velocimetry
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Additional Information Eligibility criteria In addition to a PhD in astrophysics, the candidates must have a solid background in stellar spectropolarimetry and / or velocimetry to efficiently analyze spectra
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ExperienceNone Additional Information Eligibility criteria PhD in Earth/environmental sciences/remote sensing with applications in AI Linux, Python, good command of English Additional comments Nothing to mention
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Information Eligibility criteria Education: PhD in tissue engineering, bioengineering or cell biology. Technical skills: experience in cell culture and organoid production, immunolabelling, PCR. Microfluidics
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candidate who has a strong quantitative background, with a PhD in Computational Mathematics, Applied Mathematics, Computational Mechanics, Geosciences, Acoustics or Simulation engineering. The candidate
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molecular biology, conventional and spectral flow cytometry, transcriptomics, and immune assays. Candidate profile Candidates should have a PhD with strong background in Immunology, expertise in animal
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engineeringEducation LevelPhD or equivalent Skills/Qualifications We are looking for an enthusiastic researcher with a PhD in Polymer Science, Materials Science, Chemical Engineering, Mechanical Engineering, Chemistry
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. · Location: CEA LITEN – INES Site, Le Bourget-du-Lac, France You should hold a PhD in Energy Engineering, Mechanical Engineering, Thermodynamics, Fluid Mechanics, Process Engineering, or a related field. We
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hold a PhD in the fields of ecology or evolutionary biology, or biostatistics/biomathematics. Required skills: - Data analysis using R and database management - Statistical modelling for ecology