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epigenomics, metabolomics, single-cell technique, bioinformatics, genetic animal models, molecular and cellular biology, metabolic tracing, sophisticated virus tools, neurobehavior, opto/chemogenetics, in vivo
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Biostatistics & Bioinformatics Duke University invites applications for a postdoctoral associate in scientific machine learning (SciML) as part of a new NIH-funded Center for Excellence in Multiscale Immune
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analyses (bioinformatic and statistical) of environment and microbiome data, including amplicon sequencing libraries, metagenomes, and metatranscriptomes. • Publish (as lead and co-author) in leading
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We are seeking a 100% time on-campus postdoc to conduct research in the area of legume crop genomics and bioinformatics. Post-Doctoral Associates conduct research and/or service that provides further
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physiological balance. Perform LC/MS based proteomic analyses of circulating proteins and assess their impact on organs in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic
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biochemistry, bioinformatics, single cell genomics, epigenetics, pharmacology and pathology. The Nelson laboratory website provides additional information: https://research.fhcrc.org/peternelson/en.html
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regulatory genomics. Proficiency in R, Python, or other programming languages, experience in bioinformatics analyses of NGS data and understanding of statistical principles is highly desired. Experience
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bioinformatic tools, including phylogenetics and methods for inferring signatures of natural selection. The position is supposed to be filled at the earliest possible date and initially funded for 2 years with
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interactions with drastically increased scale and efficiency. The ideal candidate has experience or a strong desire to build bioinformatics tools for interpreting high-throughput mass spectrometry or DNA
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culture of scientific excellence, teamwork, and rigorous innovation Qualifications: Ph.D. in Computer Science, Computational Biology, Bioinformatics, Pharmaceutical Sciences, or equivalent In-depth