Machine Learning Scientist

LI-EP1

You will be joining Inception Labs, a research and development team within Recursion. This team is a cross-functional group of exceptional biologists, engineers, product managers, machine learning scientists, computational biologists, and data scientists. Together, we are working to prove out novel technologies including new biological assays and data modalities, statistical and ML techniques, and computational approaches for multimodal data. This team works rapidly on a project-by-project basis to either prove or disprove the value and feasibility of these new ideas and approaches.

Recursion has built a unique dataset (over 1 million unique biological perturbations profiled in a high-dimensional biological assay, making up nearly 20 PB of highly-relatable data) and a unique approach to phenotypic drug discovery using our inference-based Recursion Map to predict tens of billions of relationships between disease models and therapeutic candidates. Additionally, we’ve generated additional large-scale Omics datasets to complement our phenomics data.

Recently, Recursion has also gained access to large numbers of anonymized patient records including medical imaging and molecular profiling artifacts to guide our understanding of disease mechanisms. The capabilities you bring to the Inception Labs team will help us scale our machine learning models using these and other data sets to develop net-new capabilities that don’t currently exist!

• Expert knowledge in machine learning theory & practice and its applications to challenges in biological or medical science including the ability to:
• Ideate and scope net-new impactful ML-based projects that can impact drug discovery
• Coordinate with stakeholders and teammates as well as contribute directly to execute on projects
• Develop net-new algorithms and architectures, particularly leveraging self-supervised and multi-modal learning
• Experience with one of but ideally multiple types of biological data (microscopy, histology, transcriptomics, clinical data)
• Run quick and focused computational experiments evaluating project feasibility
• Work closely with biologist to develop new training and benchmarking datasets
• Interpret and develop benchmarks for assessing model performance
• Tools:
  PyTorch, Num Py, Pandas, GCP, Hybrid Cloud, Linux, CUDA, Docker, Kubernetes, Big Query, large scale distributed systems

• You will join an interdisciplinary team that’s having a major impact internally and externally
• You will contribute to conference publications and have the opportunity to attend major ML conferences
• You will collaborate with other cutting edge teams at Recursion, including Valence Labs at Mila in Montreal