Scientist/Sr Scientist, Computational Biology

Prime Medicine
Research & Development
United States Massachusetts Cambridge


Prime Medicine was founded in 2019 with a clear and explicit purpose: to deliver on the promise of prime editing; an exciting, next-generation gene editing technology, which may be used to more effectively treat or halt the progression of many different genetic diseases. Prime editing is a technology that acts like a DNA word processor, with the power to “search and replace” disease-causing genetic sequences at their location where they are found in the genome (in situ), all without making double-stranded breaks in DNA. It has the potential to restore nearly 90 percent of known disease-causing genetic mutations back to the wild-type, or healthy, form. We are applying a data-driven, patient-first approach to inform our preclinical and drug development efforts: initial areas of focus will be selected based on rigorous scientific interrogation and what is best for patients. Our company is led by a world-class team, including leaders who developed prime editing and executives with deep experience in company building, research and clinical development, and supported by a strong investor syndicate.

Position Overview

We are seeking a motivated computational biologist with broad skills in genomic analysis and scientific interpretation to join our team at Prime Medicine. You will partner closely with Discovery Research to develop hypotheses, design experiments, build bioinformatic methods, perform statistical analyses, and apply machine learning where applicable. We seek individuals driven by scientific curiosity and a deep interest in changing patients’ lives.

Primary Responsibilities

- Contribute to multiple stages of drug discovery by interrogating omics datasets with an emphasis on DNA and RNA NGS datasets
- Utilize pathway exploration and systems biology approaches to understanding diseases
- Proactively find solutions to scientific challenges
- Show strong team spirit and focuses on finding collaborative solutions
- Develop and implement algorithms and analyses of molecular, cellular, and phenotypic datasets
- Implement machine learning and/or statistical approaches to large-scale molecular, cellular, and phenotypic datasets
- Communicate findings, plans, publications internally and externally in scientific or technical journals and/or conferences
- Identify new opportunities in latest scientific literature; incorporate new knowledge into current projects; learn new skillsets in computational analysis
- Manage interactions with external academic collaborators, consultants
- Set clear priorities, manage many projects effectively
- Ready to roll up sleeves and get stuff done in a fast-paced startup environment


- M.S. or Ph.D. in Computational Biology, Bioinformatics, Biostatistics/Statistics, Computer Science, Mathematics, Genetics, Molecular Biology or a relevant scientific field with direct experience in computational biology
- 2+ years’ experience, preferably in a drug development setting
- Deep expertise in NGS analysis (genomics, transcriptomics, single cell, etc.)
- Strong experience with statistical and machine learning methods with large-scale datasets
- Strong publication record
- Strong coding skills using Python, R, git, Jupyter
- Proficient with high performance computing, preferably on public clouds (i.e. AWS, GCP, Azure, IBM
- Experience with human statistical genetics analysis is a plus (i.e. GWAS, PWAS)
- Familiarity with protein structural modeling is a plus
- Demonstrated ability to work collaboratively in teams
- Evidence of maturity, self-awareness
- Strong written/verbal/listening/interpersonal skills

Start date

To be determined

How to Apply