Senior Scientist, Machine Learning Antigen Design

Apriori Bio is an early-stage biotechnology company with an ambitious and exciting mission: to lay the foundation for Global Pathogen Shield™ protective interventions that that can neutralize a wide range of the most dangerous and rapidly evolving infectious pathogen threats. The company is developing a revolutionary approach to this challenge and recruiting a team of top-tier scientists to build what it believes will be a powerful, first-in-category R&D platform.

Apriori Bio was founded by Flagship Pioneering, a biotechnology company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

Position Summary:

This Senior Scientist will join a rapidly growing team leveraging computational approaches to design novel antigens and evaluate subsequent vaccine responses. The successful candidate will play a key role in formulating and executing upon a science & technology strategy that will allow the company to deliver against its near- and longer-term goals. Expertise in developing computational inference approaches (biophysical, statistical, ML/AI) that incorporate data from high-throughput functional genomics assays (e.g. deep mutational scanning, barcode-based NGS assays, and other library-based phenotypic screens) is desired, as is technical expertise in protein engineering, virology or vaccinology. This candidate will also collaborate with other experimental and computational scientists to interpret results in the context of additional, state-of-the-art immune profiling datasets. This individual will join an interdisciplinary and collaborative team at the interface of computational immunology, virology, functional genomics, and vaccine design; they should be comfortable communicating and working with diverse backgrounds in a fast-paced startup environment.

Key Responsibilities:

• Design, train, and apply models that integrate high-dimensional datasets from biological screening platforms with structure- and sequence-based approaches to guide biomolecule engineering
• Formulate hypotheses and design experiments to evaluate novel immunization strategies
• Identify and source relevant external datasets to support the vaccine design program
• Build robust computational tools for data-driven product design that can be easily integrated into our platform
• Collaborate with engineers, computation scientists, and experimentalists to execute on project goals
• Collaborate with in vitro and in vivo characterization teams to interpret vaccine immunogenicity in context of next-generation immune monitoring tools
• Communicate insights and conclusions to colleagues in the scientific and leadership teams

Basic Qualifications:

• Ph.D. in biomolecule engineering, immunology, computational biology, or a related field with 5+ years post-PhD experience 
• Experience with applying biophysical, statistical, or ML/AI approaches to interpret and apply readouts from high-throughput phenotypic screens
• Expertise in biomolecule engineering (structural, rational, or machine-learning driven) with applications in vaccine or protein design
• Strong scientific/quantitative programming skills (python preferred) and experience in implementing best practices in reproducible scientific computing
• Experience with collaborative coding in an academic or industry setting

Preferred Qualifications:

• 3+ years of experience leveraging high-throughput phenotypic data for biomolecule design
• Experience in vaccine design, optimization, and/or selection, especially against highly variable viruses
• Experience with machine learning, especially deep learning
• Experience with NGS data pipelines and analysis
• Experience with cloud and/or distributed computing
• Laboratory experience in molecular biology, biochemistry, or immunology

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.