We are looking for a motivated Computational Biologist to join our interdisciplinary team in the Department of Biomedical Informatics at Harvard Medical School, for an exciting opportunity in building data analysis tools and pipelines for clinical genomics. Genome sequencing is becoming a routine approach for diagnosing genetic diseases, as well as discovering new disease mechanisms. As the number of patients referred to genetic screening is increasing, there is a clear need to build effective solutions to manage their data for clinical applications. The same data also provides opportunities for research and discovery. The Clinical Genomic Analysis Platform (CGAP) at Harvard Medical School is envisioned as scalable research and clinical web-based application for analysis, annotation, visualization, and reporting of genomic data. CGAP is developed by a multidisciplinary team of clinical geneticists, bioinformatics scientists and software engineers. The working environment combines the best features of a startup (fast pace, flexibility, flat hierarchies) with those of one of the leading medical schools (excellent benefits, outstanding opportunities for learning, great resources, brand recognition). CGAP is currently seeking a full-time Bioinformatics Scientist to enhance the analysis of DNA sequencing data for our growing Genomics Program. The scope of this role will include developing, automating, and implementing leading-edge genetic software tools. These tools will facilitate the identification and annotation of disease-causing genetic variants of patients at the clinic.
- Ph.D. in Biology, Bioinformatics, or a related field; or a master’s degree and 3 years' experience in Bioinformatics.
- Technical expertise in genetics, molecular biology, bioinformatics or related field.
- Strong programming skills.
- Proficiency in LINUX operating systems and related scripting languages.
- Proficiency in Python.
- Experience in high-performance computing, clusters, and cloud computing.
- Experience with software development for healthcare products as well as familiarity with common clinical scenarios, regulatory and quality standards, payer and provider considerations.
- Research experience in genomics or population genetics.
- Analysis of high-throughput sequencing data.
- Software pipeline management.
- Version Control, in particular Git.
- AWS environment.
- Web development.
- Open-source software development.
- R, C/C++, Java