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Field
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techniques, mouse models, human specimens, and bioinformatics. We are looking for applicants with wet lab immunology research experience driving the successful completion of projects and authoring peer
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. Department Specific Qualifications Education: PhD in biostatistics, statistics, bioinformatics, computational biology, or a closely related quantitative field awarded within the last five years. Experience
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imaging is also required. However, experience with bioinformatics or computational tools for biology is highly recommended but not required. This position provides an opportunity to lead and run experiments
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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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publication: computational biology/bioinformatics, cheminformatics, analytical chemistry/mass spectrometry/metabolomics, or machine learning/computer science.Term of appointment is based on rank. Positions
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in the field of microbial ecology, molecular biology, microbiology or comparable with and a very good PhD Professional experience as a postdoc and experience in the supervision of qualification theses
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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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the possibility of renewal subject to funding availability and satisfactory performance. Applicants should possess a PhD degree in Biology or related disciplines, preferably with experience in virology research
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postdoctoral associate with expertise in computational biology and/or bioinformatics to join our interdisciplinary group studying the functional genomics of tandem repeat expansions and related structural
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interpretation of OMICs datasets (DNA, RNA, proteome) Supervision and technical guidance of Bachelor’s, Master’s, and PhD students, as well as technical staff within the project context Participation in teaching