Scientist I, Computational Biology

CRISPR Therapeutics•South Boston, MA

1d•Hybrid

About The Position

CRISPR Therapeutics is seeking a Computational Biology Scientist to join its Genomics and Computational Biology team. The role applies computational genomics to advance next-generation gene-editing therapies toward clinical use. Work includes characterizing gene-editing safety, addressing complex bioinformatics and computational biology problems, and maintaining and developing computational infrastructure, analysis platforms, and internal web applications. The scientist will collaborate with cross-functional research groups and is expected to bring strong computational biology and genomics skills, scientific rigor, attention to detail, and a commitment to creating new medicines for patients. CRISPR Therapeutics is a biopharmaceutical company developing gene-based medicines for serious human diseases. Its pipeline spans hemoglobinopathies, cardiovascular, autoimmune, oncology, regenerative medicine, and rare diseases. The company is headquartered in Zug, Switzerland, with U.S. and R&D operations in Boston, Massachusetts, and San Francisco, California. Employees work at least three days on-site, balancing remote-work flexibility with in-person collaboration; certain lab-based and manufacturing roles are fully on-site.

Requirements

Ph.D. in computational biology, bioinformatics, genomics, computer science, or a related field, with 0–2+ years of industry experience; alternatively, an M.S. with an exceptional track record and eight or more years of relevant experience.
Demonstrated record of developing successful computational pipelines for high-throughput DNA sequencing data and using common bioinformatics tools such as BWA, SAMtools, BEDTools, GATK, and IGV.
Proficiency in Python.
Experience with Linux and large-scale genomic datasets, and working knowledge of developing and maintaining computational infrastructure in a cloud-computing environment such as AWS.
Ability to work independently and effectively in a matrix environment, prioritize and manage multiple tasks simultaneously, and balance competing priorities.
Commitment to scientific rigor, accuracy, and meticulous attention to detail.

Nice To Haves

At least two years of industry experience developing bioinformatics tools for gene-editing and/or clinical diagnostic applications.
Familiarity with R, Java, and workflow managers such as Nextflow.
Proficiency applying NGS tools to characterize on-target, off-target, and translocation profiles of gene-edited cellular products.
Familiarity with sequencing platforms including Illumina, PacBio, Oxford Nanopore, and 10x Genomics, and with NGS library-preparation methods.
Experience with web-development frameworks such as Django or Flask, front-end frameworks such as React or Angular, and relational databases such as MySQL.
Proficiency with statistical and machine-learning methods and experience applying them to genomic data.
Excellent writing and presentation skills, including the ability to author rigorous scientific reports and communicate findings to diverse audiences; demonstrated experience authoring reports supporting regulatory filings such as IND modules and Investigator's Brochures.

Responsibilities

Lead computational biology and genomics activities in a cross-functional drug development setting.
Develop and implement computational biology pipelines and methods in collaboration with cell and molecular biologists to support therapeutic development and research.
Perform computational analyses to characterize off-target gene editing and support the safety of CRISPR-based drug products.
Generate and test hypotheses on genome-scale data using analytical and statistical methods.
Author scientifically rigorous research reports for IND submissions and other regulatory filings, and present findings to leadership to inform therapeutic-program decisions.
Maintain and develop computational infrastructure and platforms for reproducible genomic data analysis, including dedicated cloud-computing environments.
Maintain and develop internal web applications that make analysis methods and results accessible to scientific stakeholders.