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promising properties. The project could be combined with experimental work if this is a fit for the applicant. Your profile To be eligible for employment as a postdoctoral researcher, a PhD or a foreign
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Center for Immunology of Marseille-Luminy (CIML) | Marseille, Provence Alpes Cote d Azur | France | 15 days ago
data quality Participating in project meetings and contributing to scientific publications Required Qualifications PhD in Cell and Molecular Biology, Immunology, or related field Strong skills in
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the UK Visas and Immigration Website. We are seeking a highly motivated researcher with a PhD in a relevant discipline (such as microbiology, neuroscience, bioinformatics, or systems biology) to join our
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Overview Qualification type: PhD Subject area: Microbiology and crop protection Location/Campus: Hatfield, College Lane Campus Start date: 1 September 2026 Closing application date: 10 March 2026
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vectors studies, including vector design and cloning. RNA sequencing. Proteomics/transcriptomics and bioinformatics. PLA. Immunohistochemistry on brain sections. Surgery to implant electrodes and EEG
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Initiatives in Forest Research (https://www.slu.se/wiforce ), was created. Department of Wildlife, Fish, and Environmental Studies We are seeking a highly motivated PhD candidate to join the TRACE-AIR project
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systems (iPSC and human brain samples) and multi- level technical approaches to address questions at the molecular, cellular, bioinformatic, and behavioral levels. Salary will be commensurate with research
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details. Read about the PhD education at SLU at https://www.slu.se/en/study/programmes-courses/doctoral-education/ Academic union representatives: https://internt.slu.se/en/my-employment/employee
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PhD Position - Marie Curie network MetaExplore: Functional metagenomics - novel biocatalysts for a sustainable circular economy from ultrahigh throughput screening. A doctoral position is available
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Department/Location: Department of Biochemistry, Central Cambridge PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based