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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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data and offers a broad range of online and in-house bioinformatic pipelines for analysing bacterial and viral genomes and metagenomes. The group has already back in 2013 developed a bioinformatic
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biology, cancer biology, molecular biology, immunology, and bioinformatics are all welcome to apply. Lab techniques include mammalian cell culture, mouse models, standard molecular biology and biochemistry
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transplantation and viral immunity. Apply and expand expertise in advanced methodologies such as CyTOF, sequencing approaches (CITE-Seq, NGS, RNA-seq), and bioinformatics, with opportunities to learn and integrate
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, untargeted metabolomics, quantitative proteomics. Computational and AI approaches: microprotein bioinformatics, multi‑omic integration, protein language models, generative sequence design, and model
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and metabolic adaptation Identify and characterize miRNA target genes and regulatory networks using complementary molecular and bioinformatic approaches Integrate epigenetic, transcriptomic and
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, led by professor Isabel Goncalves and associate professor Andreas Edsfeldt, consists of postdocs, doctoral students, bioinformatics and laboratory engineers with both clinical and preclinical
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and museomics Strong bioinformatics skills Proficiency in command-line scripting and programming Knowledge of phylogenomics and population genetics Why conduct a postdoctoral project at the University
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aligned to these values and are looking for a Postdoc Research Associate – Computational Biology who has: a PhD in bioinformatics, computational biology, systems biology, or a related discipline strong
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nuclear calcium oscillation decoding using bioinformatic and AI approaches. The successful applicant will creatively investigate the dynamics of regulator networks at the interface of arbuscular mycorrhiza