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genomic data for reconstructing evolutionary patterns and processes that have shaped biological history across deep timescales. The ideal candidate will have a background in phylogenomics and bioinformatics
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efficacy of such efforts. Responsibilities will include activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and
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data-driven, computational approaches. Successful candidates will be willing and able to work across a breadth of disciplines - from genomics to computer science, sociology to psychology, engineering to
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in using common programming and scripting languages to analyze or otherwise use large meteorological datasets, including numerical model output, field campaign data, reanalysis, and both remote and in
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for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to develop new AI/ML approaches for anti-doping, with a focus on
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The Research Resources IT Systems Analyst plays a crucial role in supporting software applications, data and critical infrastructure needs within the laboratory animal research environment
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online at https://puwebp.princeton.edu/AcadHire/position/39421. Candidates should submit a vita, cover letter, research statement, writing sample, transcripts, and the names and contact information
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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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topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational design. Job Description We seek to hire outstanding
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on projects related to machine-learning for mass spectrometry-based metabolomics data. Positions are available starting July 2024, and will remain open until excellent fits are found. Successful candidates will