Computational Protein Design Scientist

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Who We Are
Generate Biomedicines, Inc. is a Flagship backed, privately-held biotechnology company on a mission to reimagine the drug discovery process to one of dynamic, 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 products 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.

Position Summary
We are seeking a creative, motivated Computational Scientist with background with applying computational techniques to Protein Sciences and Protein Design, who is excited about upending the traditional approach to drug development towards one characterized by intentionality, surgical precision, and speed. She/he will work with the Machine Learning (ML) group at Generate to leverage existing models for developing protein design protocols towards specific design objectives, as well as developing and co-developing new models. The role will involve building protein-generation algorithms, validating them using in-house and external data, and designing novel proteins. The successful candidate will work closely with experimental scientists from Protein Sciences and Medicines groups, to rapidly advance the scientific program.

Key responsibilities:

  • Develop, validate, and productionize protein generation protocols, optimization algorithms, and other numerical techniques, and hone them through direct deployment on our experimental platform. Use our integrated data platform to devise generation methods that leverage measured data “in-the-loop".
  • Work with Protein Sciences and Medicines groups to design proteins tailored for specific therapeutic programs.
  • Review literature and work closely with biologists to deeply understand biological domain and assay characteristics.
  • Analyze experimental data to characterize and refine generation algorithms.
  • Develop production-ready code in a team setting and present progress from scientific work in regular research meetings.

Qualifications:

  • PhD in Computational Biology, Computer Science or a related field with demonstrated experience working on protein-related applications.
  • 3+ years of experience with applying Computational and/or ML methods to problems related to protein design, modeling, or prediction, especially in relation to structure-based techniques.
  • A working understanding of protein biophysics and structure.
 
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.