56 parallel-processing-bioinformatics "Multiple" Postdoctoral positions at Nature Careers in Denmark
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interpreting large-scale spatial transcriptomic data from multiple clinical trial. You will collaborate with an interdisciplinary teams of scientists and clinicians to develop bioinformatics pipelines and tools
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-based genome editing, and bioinformatics. The lab uses diverse cell models, including embryonic stem cells and their differentiated derivatives. The research in the Choudhary group is mainly funded by
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The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in merging soil physics knowledge and data-driven modeling of soil processes and properties, starting
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Postdoc position to support international research and capacity-building projects employing elect...
assignments The successful candidate will contribute to the acquisition, processing, inversion, and interpretation of large-scale EM datasets for hydrogeological mapping in Ethiopia. The work will involve both
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across molecular biology, ecology, bioinformatics, and environmental science. The taxonomic scope is broad and inclusive: we aim to collect comprehensive data across multiple taxonomic groups to support a
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including CO2 and CH4. Responsibilities and qualifications Responsibilities: Engineer multiple enzyme properties using experimental and computational methods Set up high-throughput screening methods and
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, which also encompasses single-cell resolution spatial transcriptomics of human plaques to precisely identify and characterize disease-relevant smooth muscle cell phenotypes, a parallel track of organoid
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. The research environment is cross-disciplinary with PIs specialized in bioinformatics, biochemistry, microbiology, molecular biology and genetics. You will be working in a leading research group in legume
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of biodiversity represent three of today’s major societal challenges. Finding solutions for all these challenges requires studies that extend across multiple scales. The Pioneer Center Land-CRAFT was established in
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substantial knowledge and research experience in areas such as computational fluid dynamics, turbulence modeling, data-driven methodologies, machine learning, and parallel computing. The candidate should also