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Field
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skills in bioinformatics. Engage with an active and collaborative research community within MPIM. Visit our lab website for more information! What you need to know Please note: This position is grant
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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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of the following areas is an asset: microbiology of anaerobes and phages, assay development, functional genomics, generation and analysis of sequencing data, -omics techniques, bioinformatics, biochemistry, and
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% - Present at scientific meetings and publish in the primary scientific literature. Requirements Ph.D. in fisheries, ecology, marine biology, bioinformatics, limnology or related fields. Strong quantitative
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, scientific and numerical computation Familiarity with common Python tools including Pandas, Numpy, Scipy, Django, RDKit Doctoral Degree in Computational Chemistry, bioinformatics, computational biology, or
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analysis skills: Statistical analysis through SPSS, R, Design Expert, Origin, MATLAB, chemometric tools, or other software. Bioinformatics and grant writing. All positions are security-sensitive. Applicants
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: - Strong background in -omics techniques and bioinformatics - Experience with large-scale population genetic/genomic analyses - Strong publication record in relevant scientific journals - Ability to create
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data analysis with experience in Bioinformatics, proteomics, RNA sequencing and RNA sequencing data analysis, and multiomic integration and analysis. Development of computational analysis methods is
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biology, or a related biological discipline is required. Candidates should also have knowledge in one or more of the following areas: molecular biology, genomics/metagenomics, bioinformatics, microbiology
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Driver's License: A driver's license is not required for this position. More About This Job Required Qualifications: A PhD in Genetics, Bioinformatics, Computer Science, Data Science, Statistical Genomics