Research - Laboratory/Non-Laboratory, Staff/Administrative
Working at MIT offers opportunities, an environment, a culture – and benefits – that just aren't found together anywhere else. If you're curious, motivated, want to be part of a unique community, and help shape the future – then take a look at this opportunity.
RESEARCH SPECIALIST , Koch Institute (KI) for Integrative Cancer Research-Bioinformatics and Computing Core Facility (BCC) , to work with an outstanding group of faculty and motivated trainees. The Koch Institute is an NCI-designated Cancer Center that leverages exciting synergies between biologists and engineers to advance our understanding of cancer in order to novel develop therapeutic approaches. The facility provides bioinformatics and computational biology support to KI scientists working in more than fifty labs across four departments and centers. Will assist the BCC research computing specialist and research scientists with the development and maintenance of pipelines for sequence data production, quality control, and analysis; and apply statistical methodologies, including linear models, to biological research. Duties include programming (e.g., Perl/Python, BioPerl, Java, R, MySQL) and performing in a UNIX-based computational environment. Will also leverage expertise in machine learning and linear modelling to develop and deploy analytical routines that can be applied to BCC projects.
REQUIRED : advanced degree (MS preferred) in engineering, computer science, statistics or related discipline; expertise in a broad range of bioinformatics and computational topics such as gene expression analysis, phylogenetic analysis, machine learning, and linear modeling; formal training in statistics and two years' experience in the application of statistical methodologies, including linear models, to biological research; demonstrable expertise in programming (e.g., Perl/Python, BioPerl, Java, R, MySQL) and expertise with UNIX-based computational environments; excellent interpersonal and written and oral communication skills; experience working productively in a collaborative environment that includes both faculty and students within a university setting; and ability to work both independently and as part of a team. Job #17207
Internal Number: 17207
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