Scientist – Computational Biology (8481) – BioPoint – Cambridge, MA

Job ID: 6097
Job date: 2016-10-18

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Job Description:
BioPoint is seeking to hire a Scientist to work on a Computational Biology project in Cambridge, MA. Job Description: The Epigenetics Group is seeking a scientist who is passionate about leveraging computational biology to create life-changing therapies for patients with degenerative diseases. You will work within Epigenetics and collaboratively with other discovery, translational and clinical scientists to design experiments that probe multiple ‘omic dimensions (e.g., transcriptome, proteome, genome, epigenome), to use creative analytical approaches to reveal drug targets and biomarkers, and to generate insights into mechanisms of action. You will become expert in the interrogation of bench- and patient-derived high-throughput data sets to produce new insights into fundamental biology and to further the development of effective therapies. Qualifications: • Experience and strong proficiency in the analysis and integration of multiple ‘omic data sets • Familiarity with high-throughput sequencing platforms for analysis of: coding and non-coding transcriptomes; DNA, histone, and protein methylation; chromatin conformation; protein/RNA/DNA interactions; and/or genomics, epigenomics, or metabolomics. • A track record of working collaboratively with teams involved in large-scale data processing and analysis architectures, balancing publicly available toolsets and datasets with targeted internal code development and experimentation. • A demonstrated understanding of the use of visual information techniques to effectively communicate the essence of complex biological results. • Knowledge of statistics and modern programming techniques (including comfort in, e.g., R, Python, Java, C/C++, sh). • Knowledge of current NGS analysis algorithms and toolsets (e.g., STAR, BWA, Trinity, Tuxedo, RSEM, HOMER, MACS, GATK, Galaxy, R packages, etc.), and complete comfort using local and cloud-based UNIX compute environments. • A familiarity with linear regression, machine learning, and/or other modeling techniques, and knowledge of modern pathway and network analysis approaches. • A strong record of collaboration with cross-functional, multidisciplinary teams. • Highly self-motivated with excellent organizational, oral and written communication skills. Education: B.S. plus five years experience, an M.S. plus three years experience, or a Ph.D. Experience and/or degree in computational biology, bioinformatics, computer science, genetics, or other life sciences disciplines (background flexible). Behaviors: • Experimental design, implementation and interpretation skills • Communication skills • Creative/innovative/problem-solving • Adaptable/flexible/agile/team-oriented


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