Principal Scientist, Computational Structural Biology

Company Summary: 

Prologue Medicines, Inc. is a privately held early-stage company that is leveraging advanced biological and computational tools to develop breakthroughs in our understanding of secreted protein function and regulation in human physiology. More specifically, Prologue is pairing high throughput -omics technology with AI/ML based protein structure prediction to define and discover novel therapeutic protein biology. 

Flagship Pioneering has conceived of and created companies such as Moderna Therapeutics (NASDAQ: MRNA), Editas Medicine (NASDAQ: EDIT), Omega Therapeutics (NASDAQ: OMGA), Seres Therapeutics (NASDAQ: MCRB), and Indigo Agriculture. Since its launch in 2000, Flagship has applied its unique hypothesis-driven innovation process to originate and foster more than 100 scientific ventures. In 2021, Flagship Pioneering was ranked 12th globally 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. 

Position Summary: 

We are seeking an energetic and motivated scientist with extensive experience in computational structural biology with exceptional hands-on AI/ML computational and programming skills to provide thought leadership, strategic thinking, and critical insight to the development of new, protein-based therapies at Prologue.  The candidate would have exceptional familiarity and experience with the latest structural biology pipelines and platforms, such as Rosetta, RX diffusion, AlphaFold, ESM Fold, and be facile with leading evaluations, implementations, and testing of state-of-the-art platforms with internal data to gauge their utility at Prologue.  A strong understanding of protein modeling, ligand-structure determination, and protein-protein interactions, as well as cell signaling, bioinformatics, and biochemistry, are extremely valuable. 

The candidate should also have a background in traditional AI/ML (e.g., supervised and unsupervised techniques) and generative models and cloud environments.  Further, they should possess strong familiarity with network inference, knowledge graphs, deep learning, and generative systems using all types of biomedical data.  Creating powerful visualizations of complex data using Python, R, and other scientific programming languages is very important. 

The candidate would lead and grow a team within a larger AI and computational organization that addresses key technical challenges in harnessing the viral proteome using in silico algorithms, including predicting binding activity between proteins, leading the generation, solution, and evaluation of CryoEM structures, assess differentiation of proteins based on surface properties, employ physics-based approaches to refine and optimize lead candidates, and institute predictive models to assess the developability of prospective viral proteins.  An ideal candidate for this role would work constructively with partners from other organizations to shape, plan, and execute analyses for existing efforts while identifying innovative opportunities for altogether new approaches that create new insights and efficiencies at all stages of discovery, pre-clinical testing, and development.   

As an organizational thought leader, the candidate should also be committed to and capable of expressing complex technical material and concepts to different audiences with a focus on prioritizing strategically relevant concepts and effectively weighing their relative benefits for decision-making.  Moreover, the candidate should proactively use their technical and organizational skills to identify, organize, and initiate new internal and external activities that enable cross-functional dialogue and insight.   

Finally, the ideal candidate thrives in a small-company, fast-paced, and intellectually challenging environment. The position will provide a unique opportunity to play a critical role in the advancement of Prologue’s computational discovery and preclinical platforms, through the development of disruptive approaches for biotherapeutic drug discovery. 

Key Responsibilities: 

• Build, lead, and manage a team focused on computational structural biology and modeling, in a larger computational organization that uses insights across chemistry, biology, and data science. 

• Strategically identify, frame, prioritize, and execute projects across the entire spectrum of target discovery and pre-clinical testing that can accelerate the i