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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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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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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning
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patterns and processes that have shaped biological history across deep timescales. The ideal candidate will have a background in phylogenomics and bioinformatics of squamate reptiles; the largest group
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the following areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine
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fields. Candidate must have excellent computational and bioinformatic skills; abilities for developing simulation models will be highly valued; experience with ancient DNA genomic datasets is encouraged
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areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning
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continued funding; those hired at more senior ranks may have multi-year appointments. Experience with one or more of the following is a plus: metabolomics, bioinformatics, and/or bacterial genetics
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biophysics -experimental and/or computational genomics -computer science, statistics, and/or machine learning with applications relevant to genomics -bioinformatics -population genetics / genomics
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multi-year appointments. Experience with one or more of the following is a plus: metabolomics, bioinformatics, and/or bacterial genetics. Applications from members of groups historically under-represented