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) Positions PhD Positions Application Deadline 16 Mar 2026 - 12:00 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 May 2026 Is the job funded
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Institute for Regenerative Medicine Postdoc in Bioinformatics or Bioinformatician 50-100% Our lab at the University of Zurich studies the regulation of gene expression in stem cells and cancer. We
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application! We are looking for a PhD student in Medical Science Your work assignments As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 8 hours ago
structured exchanges with researchers to understand workflows, identify friction points, and translate user needs into technical solutions. Collaborate closely with Helmholtz AI, bioinformatics, and research
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. Bioinformatics expertise and/or experience in the biomedical field is desirable in support of the two platforms: Zhejiang Province Bioinformatics International Science and Technology Collaboration Center and the
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the building, as are key core facilities including deep sequencing, flow cytometry cell sorting and hematopathology. The candidate should have a PhD or equivalent research experience. He/she should be
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human CSF or plasma/serum using ultrasensitive immunoassay platforms, including NULISA and ELISA, with targets initially derived from RNA-sequencing–based bioinformatics analyses. In addition, the PhD
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of desert soil microorganisms and thus for maintaining microbial diversity in one of the harshest environments on the planet. This PhD position is embedded in the ERC project WinMicAct, in which we
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FieldMedical sciencesEducation LevelPhD or equivalent Skills/Qualifications Applicants should: Hold a PhD in life sciences, biomedicine, bioinformatics, computational biology, or a related field Have at least
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bioinformatics for immunology research programs. You'll work at the cutting edge of AI-enhanced immunology, applying deep learning, foundation models, and advanced machine learning approaches to understand how