Sr. Staff Scientist Bioinformatics Sequencing Application Developmen

Job Description:

Thermo Fisher Scientific Inc. (NYSE: TMO) is the world leader in serving science, with revenues of $17 billion and 50,000 employees in 50 countries. Our mission is to enable our customers to make the world healthier, cleaner and safer. We help our customers accelerate life sciences research, solve complex analytical challenges, improve patient diagnostics and increase laboratory productivity. Our four premier brands - Life Technologies, Thermo Scientific, Fisher Scientific and Unity Lab Services - offer an unmatched combination of innovative technologies, purchasing convenience and comprehensive support.

We're seeking a highly skilled individual with experience building models, algorithms, and software for analysis of next-generation DNA sequencing. The successful candidate will be part of a multi-disciplinary team developing applications for Ion Torrent DNA sequencing instruments. As part of this team, they will be expected to work in a fast paced, complex setting to hard deliverables in a collaborative environment. Critical thinking, determination to succeed, the willingness and courage to push the boundaries on the possible and the drive to deliver are key attributes. The candidate will prototype, adopt, improve, develop, optimize and validate algorithms and analysis software to analyze DNA sequencing data for oncology applications; for example, to detect low frequency variant detection in blood, to detect gene fusions, to detect deleterious deletions, etc. The candidate will participate in the design and analysis of experiments and samples needed, will report and document methods and results, will integrate methods into production software, and will collaborate with key internal and external groups.

Responsibilities:
The individual will contribute to solutions driving easy, automated analysis of human genetic variation obtained by high-throughput sequencing; will develop algorithms and applications deployed in production software for inferring biological knowledge from millions of short reads, and will optimize and validate application software. The candidate will work on applications of next generation sequencing, including some or all of the following: detection of ultra low frequency variants, detection of gene fusions, detection of deletions and other structural variants, quantitation of differential gene expression. The individual will contribute to inventing, speeding up, developing, evaluating, recommending, adapting, improving, optimizing, validating, integrating, documenting and supporting these analysis solutions. The candidate will be responsible for developing production-level software for these applications.
The candidate will keep up to date with the latest developments in algorithms for analysis of next-generation sequencing and applications of sequencing, especially for personalized medicine and human health. Other responsibilities include giving internal and external presentations, keeping abreast of the latest developments in genomics and genome medicine, and maintaining external contacts. Knowledge of bioinformatics and specific knowledge of next generation sequencing is required.

Minimum Qualifications (must have)
•PhD in computer science, computational biology, biostatistics, bioinformatics, or similar (MS acceptable for the candidate with the right experience).
•5 or more years experience building model in complex arenas, with at least 3 years of relevant experience. Demonstration of rapid prototyping experience, leading to development of production code that is robust, fast, and highly accurate.
•Ability to engage in clear written and oral communication.
•Strong programming experience in Java and/or C/C++ on a UNIX platform. A background in DNA sequencing technologies, bioinformatics, genetics, biology, and/or clinical testing, is extremely advantageous.

*LI-EB1
Preferred Qualifications (nice to have)
Strong statistical background, previous industry experience, familiarity with common bioinformatics tools, experience with high performance computing, understanding of assay design, experience working in cancer biology or human genetics or metagenomics, are all highly advantageous.

EOE


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