Machine Learning Scientist, Chemistry
Founded by Flagship Pioneering, Cellarity is the first company developing medicines through an understanding of cell behaviors. The company’s broad platform harnesses single-cell technologies and machine learning to digitize and quantify cellular behaviors, unravel the network dynamics that govern those behaviors, and generate medicines that can direct them. Cellarity is using its platform to design medicines targeting the full cellular and molecular complexity of disease, enabling a quantum leap in the success rate and speed of drug discovery, design and development. For additional information, visit www.Cellarity.com.
Are you a highly motivated and organized computational scientist who is enthusiastic about developing, learning and applying your computational skills to developing small molecules that impact complex biological systems?
You’ll get the opportunity to work in an innovative computational team, driven to deliver high impact results. You will be in an early group of pioneers developing the world's first AI platform that unveils the causes of emergent disease based on cellular understanding.
If you think you can contribute to any of these aspects/capabilities that we are building, and are keen on testing your hypotheses and learning from some of the best scientists, whilst getting to work with proprietary and relevant data sets, then we are looking for you.
- The work entails developing machine learning models to design and predict the properties of small molecules and improving the models upon rapid feedback from the wet lab experiments.
- You will be required to collaborate closely with experimental scientists from various teams to ensure that data is being fully utilized and interrogated to deliver high value readouts.
- You will be required to present your results in an interdisciplinary team of biologists, chemists, drug developers, technologists and other machine learning colleagues at company meetings and strategic program readouts
- Ph.D. or Master's degree in chemistry, chemical biology, physics, computer science, or related field.
- Practical experience in Machine Learning models, especially in Deep Learning
- A drive to (and track record of) innovate, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
- Experience in pharmacophore modeling and SAR analysis
- Experience conducting in silico or virtual screening based on pharmacophores or protein binding site structure
- Scientific understanding of molecular and systems biology, diverse molecular data types and analysis tools.
- Practical programming and scripting skills, ideally in Python.
- Fast learner, analytical thinker, creative, "hands-on", strong communication skills.
- Able to work both independently and as part of a team.
- We would like to see your GitHub repository or papers that can show case this. If you are from biotech/pharma, we would ask you share (where you can), your experiences with a focus on your role and what you specifically contributed to in a program.
- Experience with emergent behavior in complex systems, time series analysis, causal inference, domain adaptation, transfer learning, multi-modal deep learning, geometric deep learning (learning on graphs and/or manifolds)
- Ability to Google error messages and seek resolution from self investigation and/or get advice from the rest of the crew
- Interested in learning any of the above
More About Flagship Pioneering
Flagship Pioneering conceives, creates, resources, and develops first-in-category life sciences companies to transform human health and sustainability. Since its launch in 2000, the firm has, through its Flagship Labs unit, applied its unique hypothesis-driven innovation process to originate and foster more than 100 scientific ventures, resulting in over $50B in aggregate value. To date, Flagship has deployed over $2.2B in capital toward the founding and growth of its pioneering companies alongside more than $18B of follow-on investments from other institutions. The current Flagship ecosystem comprises 41 transformative companies, including Axcella Health (NASDAQ: AXLA), Denali Therapeutics (NASDAQ: DNLI), Evelo Biosciences (NASDAQ: EVLO), Foghorn Therapeutics (NASDAQ: FHTX), Indigo Ag, Kaleido Biosciences (NASDAQ: KLDO), Moderna (NASDAQ: MRNA), Rubius Therapeutics (NASDAQ: RUBY), Sana Biotechnology, Seres Therapeutics (NASDAQ: MCRB), and Sigilon Therapeutics (NASDAQ: SGTX).
Flagship Pioneering and our ecosystem companies are 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.
Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.