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Field
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, pharmacology, engineering, bioinformatics, or a related field. Preferred: Prior pharmacokinetic modeling or machine learning experience using software such as R, Python, MATLAB, GastroPlus, PK-Sim, Phoenix
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experience in molecular biology is required, especially in techniques such as DNA/RNA extraction, PCR and genomic analysis, as well as experience in data analysis using bioinformatics tools. Knowledge of next
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experimental microbiological and biogeochemical laboratory work. Generation and analyses (bioinformatic and statistical) of environment and microbiome data, including amplicon sequencing libraries, metagenomes
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of graduate students and early-career researchers in AI and multi-omics integration. Required Qualifications: Ph.D. in Bioinformatics, Computational Biology, Data Science, Artificial Intelligence, or a related
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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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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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culture of scientific excellence, teamwork, and rigorous innovation Qualifications: Ph.D. in Computer Science, Computational Biology, Bioinformatics, Pharmaceutical Sciences, or equivalent In-depth
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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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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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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