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We are seeking a highly motivated biostatistician to assist and support scientists with statistical data analysis on-going projects. This will likely include: calculation of the optimum number of animals needed for experiments, survival analysis for PI's and TCGA data, clinical data analysis, statistical data mining, statistics support for grants and manuscripts.
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The Bioinformatics Shared Resource core facility is seeking a highly motivated bioinformatician to assist and support scientists with multiple on-going genomic analyses, including data processing, visualization, and interpretation of results.
Under general direction, will create and manage a variety of data analysis projects including analysis of complex biomedical research datasets. Will solve research problems creatively, communicate results effectively, and collaborate with PIs and other team members. Will contribute to the writing of papers, reviews and grant applications.
The candidate will be expected to develop and implement analysis pipelines, in addition to providing visualization and generic summarization of different ‘omics’ data types. Analyze genomic, proteomic, transcriptomic and metabolomic datasets from raw data all the way through to biological networks, pathways and hypothesis generation, and perform all other related duties and tasks as required or assigned.
Requires a master’s degree Computational Biology, Information Systems, Human Genetics, or a related field, and a minimum of 3 years (and typically up to 7 years) of directly-related experience in genomics and/or molecular genomics, or an equivalent combination of education, training and experience from which comparable knowledge, skills and abilities have been attained. Ph.D. in a related discipline preferred.
Must have a strong background in genomics and molecular genetics with a proven track record in the form of peer-reviewed publications. Must be able to us current bioinformatic tools and have an in-depth knowledge of advanced sequencing and array-based technologies.
Must have proficiency in next-generation sequencing data analysis and experience with large genomic datasets including TCGA, ENCODE, 1000 Genomes Project, and related resources is a must. Requires knowledge of Unix/Linux environment and at least one of the programming languages (R, Perl, Python, PHP) to scripts analysis pipelines. The core largely utilizes public and commercial software tools like UCSC Genome Browser, Integrated Genomics Viewer, GenePattern, GATK, IPA, MetaCore, GeneSpring and Partek.
Requires the ability to support multiple parallel projects directed by lab investigators and contribute to the general technical knowledge of researchers at the Sanford-Burnham by giving seminars and classes on bioinformatics and data analysis.
Requires an excellent verbal/written communication and interpersonal skills, and the ability to effectively interact with individuals from various cultures and backgrounds.