What if…you could join an organization that creates, resources, and builds life sciences companies that invent breakthrough technologies in order to transform health care and sustainability?

Montai Health is a privately held, early-stage biotechnology company developing a platform for understanding and leveraging complex molecular interactions within organisms to solve global challenges in human health and sustainability. The company leverages a multidisciplinary approach that integrates tools ranging from machine learning and big data to multi-omics and high-throughput screening.

Montai Health was founded in Flagship’s venture creation engine, where companies such as Moderna Therapeutics (NASDAQ: MRNA),Rubius Therapeutics (NASDAQ: RUBY), and Editas Medicines (NASDAQ: EDIT) were conceived and created.  Since Flagship’s founding in 2000, the firm has originated and fostered the development of more than 100 scientific ventures, resulting in over $34 billion in aggregate value, 500+ issued patents, and more than 50 clinical trials for novel therapeutic agents. 

Position Summary:

We are seeking a creative and motivated Machine Learning Scientist with a strong background in computational chemistry to help build our machine learning platform. The role will involve designing, implementing, testing, and optimizing machine learning models of biological and chemical systems, and contributing to our collaboratively-developed codebase. You will work closely with other members of the computational and experimental teams to develop machine learning tools that will guide our product development. We expect the scope of the role to grow as our company scales, so we’re seeking candidates who are excited to learn new skills and adapt to changing goals.

Key Responsibilities:

  • Develop and deploy novel computational chemistry algorithms for tasks such as molecular representation learning and property prediction, compound protein interaction prediction, and predicting the activity of multiple compounds in complex biological systems.
  • Collaborate with Montai computational team to develop and maintain a robust and scalable machine learning platform
  • Expand scientific and technical expertise through familiarity with scientific and technical literature
  • Work closely with an entrepreneurial, highly-collaborative, interdisciplinary team and actively contribute to creating, shaping and executing the scientific vision of the company
  • Jump in and help with whatever is needed to get the job done: we are in this together!

Minimum Qualifications:

  • 3+ years experience in computational chemistry developing and applying cheminformatic machine learning models
  • Extensive knowledge of organic chemistry with biological applications such as high throughput screening for pharmaceutical drug development and toxicity
  • Deep understanding of biology and genetic, proteomic, and molecular datasets
  • Experience with cheminformatic and bioinformatics toolkits and libraries, such as RDKit and Biopython
  • Experience with computational representations for bioinformatic and cheminformatic objects such as molecules, proteins, and gene expression data
  • Self-motivated and curious with strong desire to both learn from and teach others
  • Outstanding communication and interpersonal skills

Recommended Qualifications:

  • PhD in computational chemistry, cheminformatics, bioinformatics, or closely related field or MS with 3+ years of industrial experience
  • Experience with deep learning, probabilistic graphical models, or other machine learning technologies and associated frameworks, such as Tensorflow, PyTorch, and Scikit-learn
  • Experience with AWS, SQL, Python, Unix shell scripting
  • Experience with machine learning infrastructure and collaborative software development through platforms like GitHub

More About Flagship Pioneering

We are creative optimists and we would love for you to consider joining our team!  See all our open opportunities across Flagship Pioneering’s Ecosystem! 

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 $34 billion in aggregate value. To date, Flagship is backed by more than $4.4 billion of aggregate capital commitments, of which over $1.9 billion has been deployed toward the founding and growth of its pioneering companies alongside more than $10 billion 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, Indigo Ag, Kaleido Biosciences (NASDAQ: KLDO), Moderna (NASDAQ: MRNA), Rubius Therapeutics (NASDAQ: RUBY), Sana Biotechnology, Seres Therapeutics (NASDAQ: MCRB), and Syros Pharmaceuticals (NASDAQ: SYRS). 

We believe pioneering is best done by teams, and that it is a process that can be taught, learned, and replicated.  Learn more about our Company Creation Model

Can Breakthrough Innovations Be Made Systematically? A Conversation With Noubar Afeyan, Flagship Pioneering’s CEO

 

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.

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.

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