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a master’s degree (if he/she applies for a position as research assistant) or a master’s and Ph.D. degree (if he/she applies for a position as a postdoc) in Bioinformatics, Computational Biology, or
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of the Medical University of Vienna. With around 6,500 employees and 8,600 students, the Medical University of Vienna is one of the largest biomedical research and teaching institutions in Europe (https
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the NEPHRON project, please refer to the webpage https://cordis.europa.eu/project/id/101171952 . What we offer At Maastricht University, you’ll work in an international, open, and engaged environment
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you will be working in an Institute renowned for its excellent scientific facilities and high-quality research. For further information, please visit: https://www2.mrc-lmb.cam.ac.uk/group-leaders/t-to-z
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recommendation by CNN (https://edition.cnn.com/travel/article/aarhus-denmark-things-to-do/index.html ). Aarhus is easily reached via local international airports in Jutland within 1 hour of Aarhus, or via
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Three-Year Postdoc Opportunity in Ecosystem Structure, Functions and Services in Offshore Marine ...
candidates regardless of personal background. Application deadline: 1st of May 2026 at 23:59 hours local Danish time Please see the full call, including how to apply, on https://fa-eosd-saasfaprod1
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these disciplines. Read more here: https://www.sdu.dk/en/om-sdu/institutter-centre/fysik_kemi_og_farmaci/ominstituttet Application deadline: 21 January 2026 at 23:59 hours local Danish time Please see the full call
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portal (https://jobs.vib.be/apply/130479 ) before 28 February 2026. Please, provide your CV, 2 reference contacts and a motivation letter.
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, epidemiology, biostatistics, statistics, computer science, machine learning, or another related statistical or computational discipline Creative, thoughtful, and a communicative collaborator Familiarity with
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networks (PMID:26655834, PMID:34106209, PMID:39009834 and BioRxiv. https://doi.org/10.64898/2025.12.01.691495). The importance of Arp2/3 complex subunit isoforms is evident from the observation that loss