Principal Scientist, Computational Structural Biology

Key Skills

Aartificial intelligence, Deep Learning, Large Language Models - LLMs, Leadership Skill, Machine learning techniques, Planning and organization, Python Programming, PyTorch, R Programming, TensorFlow

Job Description

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 identification and optimization of prospective viral proteins against human targets.
• Work seamlessly across knowledge graphs containing external, public-domain data and novel measurements generated by internal laboratory experiments.
• Lead internal collaborations with cross-functional partners and stakeholders using advanced analytical techniques to predict physiochemical properties in silico and de-risk the development of protein-based therapies.
• Stay on the leading edge of structural biology, including protein folding, alignment, and clustering and ligand binding, and introduce latest computational tools and methods into the Prologue ecosystem.
• Lead and contribute to AI/ML and software development best practices within Prologue, including data management, cloud-based platforms and security, and version control.
• Contribute to scientific publications and intellectual property disclosures.

Minimum Qualifications:

• PhD in structural biology, computational biology, bioengineering, or equivalent.
• 6+ years of industry experience in drug R&D in pharma/biotech or life science-related industries with past experience involving both technical and strategic leadership
• High proficiency in developing and/or implementing AI/ML models in Python and R, particularly generative protein design, knowledge graphs and semantic modeling and inference, supervised/unsupervised learning, and LLMs. Experience with ML frameworks for deep learning (e.g. PyTorch, tensorflow, keras, MXNet) & cloud platforms.
• Demonstrated evidence of strong, structural biophysical expertise in the areas of protein folding, protein-protein interactions, and protein function estimation, particularly AlphaFold, ESM, USalign, Rosetta, RF Diffusion, etc.
• Publications in high impact journals, conference proceedings, or widely used codebase

Preferred Qualifications:

• Experience with structural protein design, analysis, and modeling.
• Experience with generative AI capabilities for lead optimization.
• Past experience in drug R&D in a leadership position.

About Flagship

Flagship Pioneering is a bioplatform innovation 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.

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.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.