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background in gene regulation and 3D chromatin organization in glioblastoma, epigenetics, bioinformatics, and basic cancer biology. We are now looking for an enthusiastic and motivated postdoctoral fellow to
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Range Based on Post Doctoral Experience Type of Position Temporary Position Time Status Full-Time Required Education Ph.D. in statistics, biostatistics, data science, bioinformatics or related field
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Bioinformatics (MaCSBio). Plants constantly interact with the world around them—from light and water availability to the countless microbes inhabiting the soil. Our understanding of these dynamics is growing
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, bioinformatics, and liver disease. Based at the James Black Center, Denmark Hill campus, our team works on understanding and modeling metabolic and inflammatory processes that drive liver disease progression. We
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, and robust statistical and bioinformatic workflows across all participating sites. The role requires strong expertise in human cohort studies, microbiome sequencing technologies (e.g., 16S, shotgun
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, bioinformatics, and liver disease. Based at the James Black Center, Denmark Hill campus, our team works on understanding and modeling metabolic and inflammatory processes that drive liver disease progression. We
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the postdoctoral contract. Applicants must possess a high-quality research trajectory and a competitive publication track record. Skills: RNA biology. Cell biology. Molecular biology. Bioinformatics. Experience
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Bioinformatics and Computational Biology headed by Ivo Hofacker. Our team works on the development of algorithms and methods for problems in Computational Chemistry, Systems Chemistry, and Computational Biology
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or equivalent in Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field Special Skills, Knowledge, and Abilities: Required: Candidates must hold a doctoral degree (PhD, MD
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FieldBiological sciencesEducation LevelPhD or equivalent Specific Requirements PhD in Physics, Computational Biology, Bioinformatics, or equivalent. Knowledge of biophysics, statistical physics, machine learning