Generate Biomedicines, Inc. is a Flagship backed, privately-held biotechnology company on a mission to reimagine the drug discovery process to one of deterministic, data-driven generation. We pursue this audacious vision because we believe in the unique and revolutionary power of generative biology to radically transform the lives of billions, with an outsized opportunity for patients in need. Generate will be successful by constantly turning innovative ideas into methods, technologies, and therapeutics that solve some of the most difficult challenges with developing medicines. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us!
Generate was founded by 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 applied a unique hypothesis-driven innovation process to originate and foster more than 100 scientific ventures, resulting in over $30 billion in aggregate value. The current Flagship ecosystem comprises 37 transformative companies, including: Moderna Therapeutics (NASDAQ: MRNA), Rubius Therapeutics (NASDAQ: RUBY), Indigo Agriculture, and Sana Biotechnology.
We are seeking a creative and motivated computational scientist to expand and apply Generate’s machine learning platform to the next wave of machine generated biomedicines. You will collaborate across Generate’s platform, protein sciences, and project teams to drive new explorations in areas including, but not limited to gene therapies and cell therapies. You will expand, build upon, and contribute to Generate’s core code base while applying the existing technology to new platform development and technological capabilities. The successful candidate will be a generalist computational scientist with a natural affinity towards an exploration mindset and pushing technology into unknown biology.
- Rapidly prototype and evaluate Generate’s machine learning platform applied to new modalities
- Generate and iteratively optimize protein or biological system designs across multiple projects
- Quickly ramp up expertise in new biological systems, diseases, and computational technologies
- Synthesize results and recommendations into documents and presentations for a variety of audiences from R&D updates, BoD materials, and investor decks
- PhD in Computational Biology, Genomics, Biology, Machine Learning or a related field with demonstrated experience applying ML to biological applications
- Experience applying machine learning methods to biological problems, with a particular emphasis on multi-component or multi-scale biological systems
- Evidence of innovation at the intersection of ML and protein science, gene therapy, immunology, cell engineering, and/or genomics.
- Experience developing, debugging, and applying models using modern deep learning frameworks
- Proficiency in Python and experience analyzing data with Numpy/Scipy, R, or similar
- Ability to parallel process multiple projects and work streams
- Entrepreneurial, thrives in fast-paced environments
- Outstanding verbal and written communication skills
- Unmatched sense of urgency
- Optimistic and innovative; solution-oriented; shows no signs of cynicism
- Values, communicates and interacts with others with high levels of transparency and respect