Opportunities

Graduate Students

We currently have openings for funded graduate student positions, for individuals who are already admitted to a graduate program at Harvard Medical School within the Harvard Integrated Life Science programs, or Harvard University. Please email CV and statement of interest to ccassa@bwh.harvard.edu.

Position available: Postdoctoral Fellow

Postdoctoral fellowship available related to predicting the clinical impacts of genetic variants in established disease genes, such as BRCA1 and LDLR. Projects involve methodological development and analysis of large-scale clinical sequencing and experimental datasets. Experience in computational genetics, human genetics, or statistical genetics would provide a helpful background. However, we will consider all applicants with a strong quantitative background excited to work at the forefront of this rapidly expanding field. Please email CV and statement of interest to ccassa@bwh.harvard.edu.

Position available: Associate Computational Biologist for Early Career Researchers

The Cassa and Sherwood Labs at Brigham & Women’s Hospital and Harvard Medical School invite applicants for the position of associate computational biologist, developing computational-experimental approaches for genetic risk assessment. The ideal candidate will have strong interest in developing computational methods to better understand human disease, by analyzing data from CRISPR screening assays and/or large population genomic datasets. The ideal candidate will be familiar with common bioinformatics tools, be comfortable developing new models and methods in Python, and have some experience in statistical analysis. The role requires strong problem-solving skills as well as the ability to efficiently communicate and interact with collaborators from clinical, experimental, and computational backgrounds.

The research in our groups covers a wide variety of scientific areas. Your role will include a combination of the following duties:

  • Apply existing and novel algorithms to genomic data sets, analyze data quality, critically review and analyze results, communicate results to biologists, computational biologists, software engineers, and clinicians.
  • Develop data analysis strategies or new algorithms, and deploy computational tools for the exploration of very large data sets.
  • Explore novel data visualization tools, with an emphasis on integrating diverse data types or sets
  • Implement or improve algorithms in software tools for distribution to the global research community
  • Apply machine learning techniques to develop new models

​ You will take a hands-on, problem-solving approach, and collaborate with engineers and scientists in an informal collegial work environment infused with intellectual rigor. The right candidates will have an outstanding academic record, strong communication skills will demonstrate innovative/analytical thinking and will enjoy working in an interdisciplinary team. The BWH Division of Genetics has a vibrant research environment and provides the potential for your contributions to be used and recognized worldwide. We are looking for candidates who have:

  • Bachelor's or Master’s degree expected by Spring 2022
  • Majored in computer science, mathematics, statistics, physics, bioinformatics, biology or similar field
  • 1-4 years of undergraduate independent research experience (outside of coursework)
  • Strong programming skills and experience with programming languages, preferably Python.
  • Demonstrated effective communication skills and ability to interact professionally with all levels of staff and external collaborators
  • Proven ability to work independently with guidance and mentorship

The following experience is a plus:

  • Experience with Unix/Linux environments (including shell scripting and high performance computing environments)
  • Experience with high-throughput molecular biology data
  • Experience with analyzing large population datasets

Please send your CV and a brief letter of intent to Dr. Sherwood rsherwood@bwh.harvard.edu and Dr. Cassa ccassa@bwh.harvard.edu.