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degree in Electrical Engineering, Telecommunications Engineering, Computer Science, Applied Physics, or a closely related field Strong background in communication systems, signal processing, and applied
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-throughput and AI-driven antifungal discovery fungal symbiosis an& pathogenicity fungal metabolites, epigenetics & microbiome structuring computational microbiomics & systems biology of fungal infections
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The Computational Protein Engineering (CPE) group at The Novo Nordisk Foundation Biotechnology Research Institute for the Green Transiation (BRIGHT) is developing novel methods to engineer proteins
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Your profile PhD degree in Computer Science, Applied Mathematics, Computational Engineering, Physics, or an equivalent field with a focus on High-Performance Computing Advanced Know-How in the fields
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Doctoral (TV-L E13, 65 %) and Postdoctoral Researcher Positions (TV-L E13, 100 %) in Microbial Commu
or PhD (or equivalent) in Natural or Life Sciences (e.g., Biology, Chemistry, Bioinformatics, Geosciences, Biomedical Sciences, Biotechnology, etc.). Candidates about to obtain their degree are welcome
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interdisciplinary, and together we contribute to science and society. Your role The selected candidate will develop a computational platform to identify hierarchical combinations of cell fate conversion factors
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structures. You will work closely with computational researchers to gather data, evaluate AI predictions, and design experiments. You will work in a team with 7 PhD-students and 4 postdoctoral researchers and
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biomedical research. Required qualifications PhD in bioinformatics, computational biology, systems biology, or a related field documented experience in omics data analysis, including bulk and single-cell RNA
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at international conferences. You hold a PhD in computational biology/chemistry, machine learning or a related quantitative field. You have a solid publication record and demonstrated experience with advanced
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participating in the program will receive training in genomic analysis, experimental modeling, translational science, and preclinical modeling of childhood hematological malignancies. The training program will