FL74, Inc. is a privately held early-stage company that is applying machine learning and artificial intelligence (AI) to transform the way we create and grow breakthrough insights and opportunities in human health and sustainability.
FL74 was founded by Flagship Pioneering, an innovation enterprise dedicated to originating and developing first-in-category life sciences companies. Since Flagship’s founding in 2000, the firm has originated and fostered the development of nearly 100 scientific ventures resulting in $20+ billion in aggregate value, 500+ issued patents, and more than 50 clinical trials for novel therapeutic agents. These companies include Moderna Therapeutics, Rubius Therapeutics, Evelo Biosciences, and Indigo Agriculture.
We are seeking a scientist with a strong background in developing and applying Deep Learning (DL) models for problems and datasets in the biological (life sciences) domain to join our team. Candidate will help design and implement DL models, conduct analyses on biological data and ideate with a multi-disciplinary and cross-functional team to drive the development of a state-of-the-art AI engine for applications in human health and sustainability. This is an exciting opportunity to be part of a fast-paced, highly dynamic entrepreneurial environment.
- Work with FL74 team to develop and apply novel ML and DL models on heterogenous biological data
- Study internal and external datasets to address questions critical to FL74’s core objectives and generate testable hypotheses.
- Design, plan, and execute experiments that support model validation and platform development
- Develop clear, intuitive visualizations. Communicate analysis results via presentations to a multi-disciplinary audience
- Cultivate a data-centric and process-oriented company philosophy by creating and maintaining best practices for software development, data management, and infrastructure
- Monitor and evaluate new and emerging technologies and models and identify opportunities for collaboration within Flagship Pioneering companies, academia, and third-parties.
- PhD or equivalent level of experience in quantitative biology with at least one significant project leveraging machine learning (ML) methods or models. Examples include projects in system biology, transcriptomics, genomics, biophysics or neuroscience. PhD may be in (1) a field directly relevant to ML (e.g. Machine Learning, Statistics, Computer Science, Mathematics) or (2) natural sciences (e.g. Physics, Computational Biology/Chemistry, Biology).
- Knowledge and experience applying deep learning (DL) models to biological data
- Fluency in Python and standard ML tools and packages (e.g. Deep Graph Library, PyTorch, Snorkel, etc.)
- Familiarity with AWS, GCP, or similar cloud-computing services
- Motivated and team oriented, with an ability to thrive in an entrepreneurial and multidisciplinary environment.
- Ability to independently lead and run research projects, while maintaining close communication with team members
- Excellent communication and presentation skills. Must be able to speak and ideate with multi-disciplinary team including biologists. Must be able to think independently, work collaboratively and contribute to an active intellectual environment.
- Experience in one or more of the following areas/topics: graph neural networks, NLP (e.g. LSTMs, Transformers), CNNs, variational methods or GANs
- Familiarity with containerization and task orchestration tools (e.g. Docker, Kubernetes, Slurm)
- Experience working with major biological databases and datasets (e.g. TCGA) is a strong plus
Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.