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Research Assistant Professor
The University of Florida Health Cancer Center (UFHCC) consists of more than 250 basic, translational and population-based scientists and clinicians at the University of Florida who conduct research for the prevention, diagnosis and treatment of cancer. The central collaborative research model encourages the translation of basic laboratory findings to novel therapies. The multidisciplinary membership of the Cancer Center is its main strength. Researchers are drawn from throughout UF, including six colleges within the Health Science Center – Medicine, Nursing, Dentistry, Pharmacy, Public Health and Health Professions, and Veterinary Medicine – as well as the Colleges of Liberal Arts and Sciences, Engineering, Journalism and Communications, and Agricultural and Life Sciences. Research is focused around three programs: Mechanism of Oncogenesis, Cancer Therapeutics and Host Response, Cancer Population Sciences.
The University of Florida Health Cancer Center (UFHCC) seeks a Bioinformatician/Computational Biologist (Research Assistant Professor) to join us in high-quality scientific research. In this exciting role, the Bioinformatician will focus on general bioinformatics/computational biological needs of the UFHCC and UF campus. He/she will design experiments, manage data, and use advanced machine learning, as well as computational techniques. Furthermore, the Bioinformatician will collaborate with the UF investigators to guide the development of their research. This position reports directly to the Director of the UFHCC Division of Quantitative Sciences and Biostatistics Shared Resource.
Summary of Key Responsibilities:
• Proactively engage with project teams to define scientific questions that can be addressed with an appropriate experimental design;
• Support computational, machine learning or modeling capabilities needed for research projects;
• In collaboration with project teams, propose analysis strategies for target discovery, using methods based on differential expression, co-regulation, correlated amplification, recurrent alterations, and so on for integrating data from many sources;
• Identify targets and biological contexts in which treatments are likely to be beneficial by mining genetic, genomic or screening data;
• Identify biologically and clinically relevant features from patient and administrative databases (including eHealth and publicly available cancer informatics data).
• Ph.D. in a computational biology or bioinformatics related field.
• A minimum of 1+years project-based work in computational application to biology-related fields
• Programming skills in R/Bioconductor or a general-purpose language (Python, Java, etc).
An ideal candidate will be collaborative, self-directed and possess experience or expertise in:
• Collaborating with key scientific personnel and the Bioinformatics experts to build, test, adapt, support and validate analysis pipelines;
• Profiling NGS data for platform-specific patterns and synthetic data modeling;
• Creating standardized NGS datasets to be used throughout testing and validation;
• Experience developing and running analysis pipelines in a high-performance cluster environment;