At Flagship Pioneering, we conceive, create, resource, and develop first-in-category life sciences companies to transform human health and sustainability. We’ve created over 100 scientific ventures, including the now familiar drug and vaccine innovator, Moderna Therapeutics.
Since its inception in 2000, many of our companies have leveraged advances in computing, big data and AI. In recent years, this trend has accelerated with first-in-category life science companies such as Generate Biomedicines, Cellarity, Valo and many others that are creating breakthrough innovations using AI and ML technologies.
We are looking for extraordinary computational scientists, engineers, and entrepreneurs to work alongside individuals within the Flagship Ecosystem focused on solving the most impactful challenges in AI and the life sciences.
The Network ML scientist will envision and drive core research directions. They will work closely with an interdisciplinary team to design and implement novel AI solutions to problems defined on large networks in the biological science and biological publication space. This is an exciting opportunity to be part of a fast-paced, highly dynamic entrepreneurial environment.
- Work with interdisciplinary team of ML scientists to design and implement novel AI solutions to large scale networks and document corpora.
- Establish scalable frameworks for query and information retrieval over large graphs.
- Train deep graph learning models over large knowledge graphs.
- 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 in Computer Science, ML, Statistics, Math or related fields.
- Fluency with python, PyTorch, PyG, etc…
- Strong background with graph algorithms, network science, sparse matrix computations.
- Extensive hands-on experience with developing graph neural networks and working with knowledge networks.
- Fluency in Python and standard ML tools and packages.
- Strong publication record.
- Familiarity with AWS, GCP, or similar cloud-computing services.
- Experience with large graph datasets and knowledge landscaping, such as large citation data and biological knowledge graphs.
- Experience with GPU-accelerated computations on graphs.
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.*