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Field
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) Expected date of employment: March 2026 (flexible) Workplace: SAGE Laboratory (UMR 7363), University of Strasbourg, France Desired level of education: PhD Experience required: - Salary: commensurate with
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the Chair via its scientific steering committee. Candidate profile Candidates must hold a PhD (or have one by October 2025 at the latest) in one of the disciplines relevant to the Chair's research themes
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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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of the LIMASSE program, and more specifically with the LRCS (Amiens), indeed two PhD students (one at LEPMI, one at LRCS) are involved in Li-S technology in the LIMASSE project. Where to apply Website https
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with a PhD in Materials Science, Physics, Chemistry, or a related field. Prior experience in one or more of the following areas will be considered an asset: intermetallic synthesis, microscopy, x-ray
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FieldEngineeringEducation LevelPhD or equivalent Skills/Qualifications We are seeking a highly motivated and talented experimentalist with a PhD in Materials Science, Physics, Chemistry, or a related field. Prior experience
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LevelPhD or equivalent Skills/Qualifications Holder of a PhD degree in physiology, biomedical sciences, bioengineering, imaging, or related field, you have a first research experience (research engineer
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presentations and lectures. • Participate in scientific activities. FORMATION ET COMPÉTENCES Minimum level of education and/or experience require PhD in engineering or mathematics and automation or equivalent
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FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria The candidate should hold a PhD in reactor physics or an equivalent degree. He or she should: - Have a good understanding of
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have obtained their PhD in Evolutionary Biology, Paleontology or similar before commencing the postdoctoral position. Candidates must have experience in phylogenetic reconstruction (Bayesian inference