Senior Scientist, Computational Biology or Computational Oncology

The Impact You’ll Make

As part of Recursion's internal pipeline team, you will be the primary computational lead on one or more internal drug/clinical programs. You will design experiments, develop new methods, analyze and interpret results, and inform key program decisions to bring work from early‑stage hit‑identification to pre‑clinical development. You will collaborate with biologists, medicinal chemists, engineers, data scientists, and ML scientists.

• Synthesize diverse datasets (internal and external) from comp bio, med chem, target , SAR, DMPK, ADMET, biomarker discovery, etc. to accelerate programs (primarily in oncology).
• Architect analyses and experiment cascades to collect and combine data that inform statistically‑sound decisions weighing risks and benefits.
• Present and discuss data with decision makers and stakeholders in a clear and compelling way that drives medicines to patients.
• Industrialize approaches and analyses to accelerate future projects and scale impact.
• Collaborate cross‑functionally with Recursion’s data science and ML teams to advance interpretation of large‑scale phenomics data into therapeutic programs.

This is a hybrid position based at our office in Toronto, Ontario, Canada. Relocation assistance is available for qualifying candidates.

We are building an interdisciplinary group centered on machine learning and inference‑based discovery of drug programs from first principles. You will collaborate extensively with data scientists, chemists, engineers, commercial strategists, and biologists throughout the organization to advance milestones and provide insights. Essential attributes include a bold, execution‑first attitude and passion for deploying rigorous science to bring life‑changing therapies to patients.

• PhD in a relevant field (computational biology, bioinformatics, statistics, quantitative pharmacology, cancer/cell biology, etc.) with 3+ years of experience applying professional competencies to fundamental problems in oncology or drug discovery.
• Experience applying computational methods (probabilistic, statistical, and/or machine learning techniques) to analyze complex biological and/or human clinical data.
• Fluency in high‑level programming languages such as Python or R for complex data analysis.
• General understanding of small molecule drug discovery and pharmacology.
• Efficiency in advancing drug‑discovery projects, carrying and prioritizing among multiple projects, and advancing projects to proof of concept.
• Experience efficiently advancing drug program projects from proof of concept to preclinical. Industry oncology drug discovery experience preferred.
• Bold, passionate, and highly collaborative with experience working in cross‑functional teams.
• Ability to clearly explain computational analyses and methodologies to cross‑functional and non‑technical teams.
• Exceptional data visualization skills for creating plots, documentation, and presentations.

• Experience designing high‑throughput experiments to address biological questions, either independently or with bench scientists.
• Experience analyzing data from imaging‑ and/or genomics‑based modalities.
• Experience evaluating and prioritizing compounds during SAR and lead optimization cycles.

• Training on Recursion’s culture, values, and Drug Discovery & Development processes.
• Regular 1:1s with supervisor and colleagues for support and feedback.
• Opportunities to attend conferences and workshops in Oncology and/or Computational Biology.
• Multiple opportunities for leadership and mentorship training, and cross‑functional collaboration.