43 parallel-processing-bioinformatics "SciLifeLab " Postdoctoral positions at Duke University
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related field, with strong experience in molecular and cellular biology, molecular biology–related bioinformatics, flow cytometry, and cell culture. The candidate should be highly motivated, organized, and
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and analyzing multidimensional data sets Familiarity with bioinformatic and biostatistical approaches for the analysis of sequencing and proteomic data Desire to conduct team-based science in close
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independently and collaboratively in a multidisciplinary research environment. Prior experience in cancer biology is preferred but not required. Experience with mouse models, genomics, bioinformatics
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., or equivalent degree in biology, genetics, genomics, molecular biology, cell biology, computational biology, bioinformatics, immunology, bioengineering, or a related field. Candidates with experience in genomics
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: Post-Doctoral Associate Position Summary: The Department of Biostatistics & Bioinformatics (B&B) at the Duke University School of Medicine engages in methodological and collaborative research, providing
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: • Animal handling experience. • Intellectual curiosity and a growth mindset. • Biostatistics and bioinformatics expertise for scRNA-seq analysis. • Experience with molecular, cellular, biochemical, and
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process described in the Duke University Aging Center’s T32 Postdoctoral Research Training Program website (https://agingcenter.duke.edu/postdoc), AND submit an application via the link below
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Position Description The DukeNLP group in the Department of Computer Science at Duke University invites applications for a postdoctoral associate position in natural language processing and machine
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analyses of micro-randomized trials and experimental designs for Markov decision processes. The candidate is expected to innovate statistical methods and algorithms, create software implementations, carry
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cleaning, standardization, and quality assurance activities to support reproducible research. Image Processing & Annotation Preprocess ophthalmic images for machine learning applications through resizing