Recursion

The Recursion Maps of Biology are fully-relatable environments where high-dimensional profiles of genome-wide genetic and chemical profiles generate trillions of relationships between biological perturbations and potential therapeutic interventions. Recursion has developed workflows for conducting inferential discovery of relational insights from biological maps and automated the progression of these insights through the drug discovery process. This involves utilizing standardized, scaled ‘omics technologies and chemical optimization through loops of experimental data and ML predictions while continually exploring technology that can push the bounds of drug discovery. 

The Impact You’ll Make

In addition to the technological advancements that power Recursion’s ability to model complex biology across the genome, modern AI and ML capabilities have unlocked powerful tools in extracting causal biology from multimodal patient data. Leveraging these advancements, the Principal Computational Biologist will apply their creative mind to find inventive and unconventional strategies that integrate world-class patient genomics data from industry leaders such as Tempus, with Recursion's scaled and standardized experimental data. To capture the full potential of these data systems, this role will capitalize on existing state-of-the-art in AI and ML while also driving entirely new methodology in this space. We envision that taking on bold approaches to integrating patient and experimental data will reveal a greater understanding of disease biology, causality, and translational biomarkers, and will support the discovery of new, high-impact therapeutic solutions for patients.

The Team You’ll Join

This role is seated within a small, innovation-centric team at Recursion with the mission of entering entirely new frontiers of modeling, understanding and treating disease. It is dedicated to investigating new technologies and ideas that will drastically improve the drug discovery process, focusing on quickly reaching decisive endpoints. In this startup-like environment, you will take on a wide range of scientific responsibilities and join a team of dedicated scientists that all lead change through cross-functional collaboration and direct scientific engagement. You will report to the VP of Industrialized Drug Discovery and join flexible teams based on the projects at hand.

In this role, you will:

• Conceptualize and drive execution on the development of innovative AI / ML methodologies that integrate concepts from both forward and reverse genetics approaches to drastically improve the extraction of truly causal disease biology beyond what is possible with patient genetics alone. 
• Integrate new models throughout target identification, patient stratification, biomarker strategy and translational science.
• Collaboratewith other leaders across biology, chemistry, clinical development and data science to directly impact the quality and rate of advancement of our therapeutic pipeline.

Location:

This is an onsite, hybrid position that can be based in Salt Lake City, Toronto or Montreal. Relocation support is available for qualifying candidates.

What You’ll Need

• A deep dissatisfaction with the current technology available for converting human genetic data into new medicines. 
• A successful candidate will be comfortable in the unknown, possess a desire to carry projects from start to finish, and showcase an excitement to instigate change.
• 7 years applying expertise in computational biology to problems in functional and statistical genetics with high-dimensional ‘omics data, particularly aimed at problems in target identification and / or biomarker identification for patient stratification and response prediction.
• A strong understanding of modern ML techniques; able to lead and directly develop new modeling approaches
• An understanding of the overall processes and challenges in drug discovery