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to the Wallenberg AI, Autonomous Systems and Software Program (WASP). This enables interaction with researchers from different research fields and access to various scientific and technical expertise. Data-driven
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the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
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Job related to staff position within a Research Infrastructure? No Offer Description Passionate about plant stress responses, molecular biology, and bioinformatics? Join our lab as PhD candidate and
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bioinformatics is preferred. Candidates with different profiles and a strong interest in developing interdisciplinary skills are encouraged to apply. We are committed to fostering an inclusive and supportive
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2026 Apply now Passionate about plant stress responses, molecular biology, and bioinformatics? Join our lab as PhD candidate and investigate why unique plant cells respond so differently to the same
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diagnosis, and therapy of diseases like cardiovascular diseases or cancer. Overall, the institute strives to advance precision medicine by combining knowledge from different fields such as biology, chemistry
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will receive interdisciplinary training in bioinformatics, evolutionary genomics, and high-performance computing within the DDLS data-driven life science framework. Data-driven life science (DDLS) uses
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immunofluorescence, as well as the analyses of datasets within the HUNTER SDE. The Research Associate will have the opportunity to apply bioinformatic analyses to these datasets (e.g. single nucleotide polymorphisms
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of polyploid genome evolution across contrasting timescales. The student will receive interdisciplinary training in bioinformatics, evolutionary genomics, and high-performance computing within the DDLS data
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(or equivalent) in biochemistry, biotechnology, bioinformatics, chemical biology, or a related field - Strong proficiency in spoken and written English Meriting qualifications: - Experience in protein engineering