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Field
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, bioinformatics, or other related disciplines is required. Strong interest, research background and experience in the methodology research in statistical genomics, machine/deep learning, bioinformatics methods in
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and analyzing multidimensional data sets Familiarity with bioinformatic and biostatistical approaches for the analysis of sequencing and proteomic data Desire to conduct team-based science in close
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design, molecular laboratory work, bioinformatic analyses, data interpretation, and the preparation of peer-reviewed publications. The candidate will be expected to lead first-author publications and
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requirement, minimum: Ph.D. in genetics, biochemistry, cellular or molecular biology, bioinformatics,biostatistics, computational sciences, or other related fields and have prior experience in computational
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, retinal diseases, and vision science. Training opportunities may include imaging analysis, bioinformatics, statistical analysis, and grant and manuscript development. The specific training plan will be
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Computational Postdoctoral Researcher - Bacterial Genomics, Transcriptomics, and Single-Cell Genomic
, transcriptomics, and single-cell biology. Qualifications Required • Ph.D. in Bioinformatics, Computational Biology, Computer Science, Mathematics, Statistics, or a related quantitative discipline. • Candidates
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, Stem Cell Biology, Biotechnology, Biochemistry, or a closely related discipline. Candidates with experience in bioinformatics and omics data analysis are encouraged to apply. Required Related Experience
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models of infection. Experience with bioinformatics tools for data analysis. Track record of scientific publications and conference presentations. Accompanying Knowledge, Skills, Abilities and Competencies
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, Biomedical Engineering, Pharmaceutical Sciences, Immunology, Bioinformatics, Computational Biology, Chemistry, or a related discipline. Experience in one or more of the following areas is highly desirable
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advanced bioinformatic analysis; c) excited to work at the interface of human cohorts with robust epidemiologic and long-term outcomes with experimental systems; d) aim to transition to independent