The Center for Computational Biomedicine (CCB) at Harvard Medical School (HMS) is looking for an experienced Computational Biologist to advance in CCB’s mission to leverage data and computation to transform research and improve health. CCB provides computational and analytic resources to advance scientific discovery within HMS through its multi-disciplinary team of computational and quantitative scientists who work on collaborative projects both within the center and with members of the HMS community.
The role will involve processing, analyzing, and integrating public and newly generated single-cell and spatial multi-omics datasets in collaboration with experimental labs at HMS. This will include developing sustainable tools, software packages, and integrated data science products that empower research labs to explore, analyze, and interpret their data. The data sources will often be at the leading edge of scientific discovery and will therefore require methodological work, algorithm development, and technical developments.
The ideal candidate will be proficient in R and/or Python, have strong quantitative, analytical, and communication skills, and will be able to work independently and collaboratively on scientific problems and deliver solutions. There will be opportunities for working in teams and independent decision making at all levels of bioinformatic processing and statistical analysis of the data, as well as examining, evaluating, and recommending analytical approaches to collaborating labs. In addition, methodological developments for novel and challenging data analysis and integration tasks arise frequently requiring originality and creativity, including designing and analyzing follow-up experiments.
• PhD in Bioinformatics, Biostatistics, Computer Science, Statistics or related fields,
• Substantial experience analyzing genetic, genomic, or image data,
• Ability to program at a high level in R or Python,
• Ability to work independently,
• Experience with analyzing single-cell and spatial omics data,
• Working knowledge of git or similar tools for scientific software development,
• Experience writing data publishing tools that support user interaction such as RStudio’s Shiny or Connect applications,
• Experience with machine learning frameworks such as TensorFlow or PyTorch,
• Ability to work on teams,
• Strong communication skills.
Send CV and cover letter to Jaclyn Mallard