232 parallel-processing-bioinformatics-"the" Postdoctoral positions at Nature Careers
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completed PhD in (bio)informatics or (neuro)immunology A completed Master’s degree in biology, biomedicine, bioinformatics, or data science Basic knowledge in cell culture, immunology, and molecular biology
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 1 month ago
well as bioinformatic and statistical analysis is considered an asset. Demonstrated research excellence with first-author publications in peer-reviewed international journals. Strong communication skills, fluent in
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. The project is conducted in close collaboration with researchers in mathematics, ecology, and bioinformatics. The fellow will be offered affiliation and a workspace at IceLab – the Integrated Science Lab
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the following areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine
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are desirable. Candidates with additional expertise in 3D cell culture, xenografting, and/or single-cell sequencing would be highly competitive. Bioinformatic experience would be welcomed, though no prior
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, metabolomics, and bioinformatics. Postdocs have abundant opportunities to interact with a vast research community offered by Rutgers campuses and participate in various career training and activities. New
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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep
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++, Rust, or similar languages. CUDA experience is a plus. Passion for interdisciplinary research in an innovative and collaborative environment. Application Process: Submit your CV, cover letter, and
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Computational Biomolecular Dynamics Prof. Dr. Bert de Groot Am Faßberg 11 37077 Göttingen www.mpinat.mpg.de/degroot Information pursuant to Article 13 DSGVO on the collection and processing of personal data
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on Clostridium carboxidivorans and Clostridium ljungdahlii, for which we have already established robust genetic and process engineering platforms. The following publications illustrate the potential and direction