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Field
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proteomic datasets, including integration across multiple cohorts, devising workflows and strategies to plan genetic association studies. ● Conducting bioinformatics and statistical analyses of high
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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of the following: animal energetics and physiology, tissue level physiology, molecular biology, mitochondrial energetics, metabolomics, transcriptomics, bioinformatics, field research. Excellent project management
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mechanisms. Research directions include exploring DNA sequencing, DNA probe design, sequencing library preparation, bioanalytical chemistry, bioengineering and bioinformatics solutions for emerging problems in
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validations. What we are looking for PhD (or MSc with research experience) in AI, CS, Bio-engineering, or Bioinformatics. You have experience with applying AI technologies in (regulatory) genomics, as
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, Biochemistry or equivalent A publication record in peer-reviewed journals, and excellent proficiency in English for oral and written communications. Experience with bioinformatics and high-throughput approaches
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determinants of health, and integrative bioinformatics strategies, with a special focus on AI/machine learning approaches to derive new clinical insights at scale. Basic working knowledge or publication track
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). Applicants with a PhD in a quantitative field (computational biology, bioinformatics, systems biology, genetics/genomics, statistics, mathematics, computer science, or related fields) are encouraged to apply
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project funds are secured and from a non-federal source. The position involves applying bioinformatic and statistical tools to existing multidimensional datasets, including metagenomic, transcriptomic
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. The ideal candidate should have a strong background in one or more of the following: developmental biology, genetics, molecular techniques, bioinformatics/genomics, electrophysiology, calcium imaging