Are you interested in being a key member of a bioinformatics team in a shared resource at a major cancer center? This Associate Scientist position will support a wide array of bioinformatics research services in the Sylvester Comprehensive Cancer Center (SCCC) Biostatistics and Bioinformatics Shared Resource (BBSR) at the University of Miami. The responsibilities of this position include providing state-of-the-art bioinformatics and molecular informatics data analysis and expertise for clinical, laboratory and epidemiological studies, including support for gene expression analysis for transcriptome profiling and gene regulatory network building, microRNA target analysis, genome and transcriptome assembly from next generation sequencing data, SNP functionality analysis, and data visualization. Responsibilities include working closely with investigators on experimental design and high dimensional data analysis of genomics and proteomics studies for both laboratory-based and epidemiological research projects; evaluation and implementation of existing and emerging bioinformatics tools and applications; tracking project effort and milestones; and troubleshooting. Responsibilities also include direct involvement in generating publications and grant proposals that support the facility and the projects of the facility users. This position interfaces with investigators from all the Cancer Center’s research programs, and with the leaders and staff of all the other Cancer Center’s Shared Resources, which includes shared resources focused on onco-genomics, flow cytometry, biorepositories, behavioral and community-based research, cancer modeling, and molecular therapeutics. Responsibilities include providing consultation and training for the users of the Biostatistics and Bioinformatics Shared Resource, and participating in the educational workshops, seminars, and quantitative science lectures offered by the shared resource.
Qualifications: A Ph.D. degree or equivalent experience, with a minimum of 5 years of post-doctoral experience with bioinformatics and molecular informatics data analysis in support of basic, translational, clinical, and/or epidemiological studies. Must enjoy working with others, have initiative, and be reliable. Attention to detail and multitasking abilities are critical, with the ability to work both independently and as part of a team. Proficiency in R/Python programming and excellent English communication skills (both verbal and written) are required. Prefer experience with statistical and computational methodology development with application in genomics studies, with single-cell RNA/DNA sequencing and metagenomics data analysis, and with integrative multi-omics data analysis. Prefer strong critical thinking and problem solving skills with proven ability to apply creative approaches to complicated questions.
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