Company Description Unravel Biosciences is an AI-driven biotechnology company focused on understanding and treating complex diseases through its Predictable Medicine™ platform. This platform combines computational drug prediction, rapid on-demand animal models, and advanced screening technologies to connect behavioral and cognitive symptoms to new therapeutic targets within weeks. Using rareSHIFT™, a unique patient personalized analysis service that has reached more than 120 disorders, Unravel identifies drug targets across organ systems and rapidly enables clinical validation by partnering with clinicians and individual patients. The company’s lead program, RVL001, is in two clinical trials for Rett syndrome and other neurodevelopmental disorders, reflecting a strong commitment to translating discoveries into impactful therapies. Team members join a collaborative environment at the intersection of computation, biology, and medicine.

Role Description The Research Associate in Bioinformatics will support therapeutic discovery by analyzing large-scale patient and experimental datasets, integrating multi-omics data, and contributing to the identification and validation of novel drug targets. Day-to-day responsibilities include processing and curating biological data, running and optimizing bioinformatics pipelines, collaborating with wet-lab scientists to interpret experimental results, and generating visualizations and reports for internal and external stakeholders. The role also involves assisting with experiment design through data-driven insights, maintaining clear documentation of analyses, and contributing to cross-functional project meetings. This is a full-time hybrid role based in Medford, MA, with a mix of on-site collaboration and some work-from-home flexibility. Remote roles will be considered.

Qualifications

• Bachelor's or Master's degree in Bioinformatics, Computational Biology, Genomics, or a related field, with a strong quantitative and analytical background.

• Proficiency in Python for data analysis and scripting.

• Working knowledge of the Bash command line and basic scripting

• Familiarity with bioinformatics data and analysis workflows, particularly next-generation sequencing (NGS) or other high-throughput biological data.

• Basic understanding of statistical analysis and data interpretation.

• Ability to communicate effectively and collaborate in cross-disciplinary settings.

• Ability to learn new computational tools and methods and work independently on well-defined problems.

Preferred Qualifications

• Working knowledge of R for statistical analysis and biological data analysis.
• Experience with workflow management systems, ideally Nextflow
• Experience with common bioinformatics tools and packages relevant to NGS data analysis.
• Experience working with computational infrastructure, including high-performance computing (HPC) clusters, cloud computing platforms (e.g., AWS), or other distributed computing environments.
• Experience with Git and version control.