48 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "P" 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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. Benefits and salary The successful candidates will receive an attractive salary in accordance with the MSCA regulations for Early-Stage Researchers (http://ec.europa.eu/research/mariecurieactions
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websites. Application Process Applications for both programs must be submitted online by January 14, 2026: https://www.uni-goettingen.de/de/application/556704.html Applicants will be asked to upload a CV
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Registered Report, see https://www.nature.com/articles/s41562-021-01193-7) • Communication and teamwork skills, commitment, autonomous working style, attention to detail, willingness to be time-flexible
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history, list of publications, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) Applications received after
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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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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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( https://doukalab.univie.ac.at/ ) on a research project supported by the European Research Council. They will be part of a leading international team of researchers in the department working across
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Information about union representatives, see Help for applicants . Application procedure Apply via LiUs webpage for vacancies, https://liu.se/en/work-at-liu/vacancies/28629 . Your application must reach
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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