92 structures-"https:" "https:" "https:" "https:" "https:" "https:" "Ruhr Universität Bochum" PhD positions at Nature Careers
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events are foreseen, applicants must be ready to travel Applicants must be eligible to enroll on a PhD program at TU Dresden (see https://tu-dresden.de/ing/maschinenwesen/postgraduales/promotion
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one of 18 structured Ph.D. programs that provide a defined academic framework while allowing you to develop your own research focus. Applications are submitted for specific projects, and you should meet
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various plant and algal species, and follow an interdisciplinary approach, combining molecular biology, genetics, epigenetics, metabolomics, biochemistry, structural biology, biophysics and microscopy with
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-year contract starting September/October 2026 https://www.eu4greenfielddata.eu/ APPLICATIONS OPEN ON Juanary 5th 2026 Are you an aspiring researcher ready to drive the digital and green transition in
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(XRD) to characterize, at the molecular level, smectite samples from various Swedish mineral deposits. The PhD student will be part of a research group active in the area of molecular geochemistry (http
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English – written and oral We offer: a stimulating, world-leading research environment on biomolecular condensates embedded in a focused, interdisciplinary structured training program with close mentoring
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applicants in accordance with European and German legal regulations. Further information on data protection and the processing of personal data can be found at: https://www.isas.de/en/datenschutz . The closing
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vitae (max. 3 pages), structured as per TENK guidelines completing the sections relevant for applicant’s career stage and the target position. Two reference letters submitted by the referees via
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(https://www.cliccs.uni-hamburg.de/about-cliccs/cliccs-ll.html ). In CLICCS-M4, we are further developing the unique ICON-Coast model within the ICON Earth System Modelling Framework. The objective
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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de