The Scientist II, Computational Biology on the Computational Biology Team provides computational, bioinformatic and statistical activities to enrich the analytical capabilities of existing products as medical knowledge advances, as well as to design and build lab protocols and computational analyses for new products.
Key Responsibilities
Work within an interdisciplinary team of molecular biologists, computational biologists, software engineers, and scientific leaders focused on developing diagnostic products using massively parallel sequencing of tumor genomic DNA and RNA.
Lead development of algorithms and new computational methods for identifying clinically-relevant alterations in tumor DNA and RNA derived from clinical cancer specimens.
Enhance and optimize existing methods, improving their assay capabilities as well as their technical robustness.
Oversee collaborative software development and validation efforts.
Process, analyze, and interpret high volumes of data for the development and validation of methods.
Incorporate new findings of cancer biology and diagnostics into existing computational pipelines.
Monitor and evaluate analytical aspects of new and emerging technologies.
Present scientific and technical data to colleagues in a clear and cohesive manner.
Work independently and prepare timetables, deliverables, and project schedules.
Mentor junior colleagues and collaborate with project subteams.
Other duties as assigned.
Qualifications
Basic Qualifications:
Master's Degree in Bioinformatics, Computational Biology, Computer Science, or a related field
2+ years working in NGS based diagnostics or research
Academic or professional study/work with molecular biology and/or genomics
Familiar with one of the following programming and scripting languages: Python, Java, R, or C++
Preferred Qualifications
PhD in Bioinformatics, Computational Biology, Computer Science, or related field
Strong understanding of molecular biology and genomics
Experience:
contributing to a complex production analytical system
developing algorithms for analysis of biological data
with next-generation (NGS) sequencing data
in cancer research, including a working understanding of computational approaches for cancer genome analysis
Excellent teamwork, time management and organizational skills
Demonstrated ability to: work independently in a multidisciplinary, fast-paced, dynamic, and results-oriented environment present data to a multidisciplinary audience in a clear and cohesive manner
Understanding of HIPAA and the importance of patient data privacy
Commitment to reflect FMI's values: passion, patients, innovation, and collaboration
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Research, Analyst, and Information Technology
Industries
Biotechnology Research
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