Lead Scientist in Computational Structural Biology

2 weeks ago

Cambridge, Massachusetts, United States Flagship Ventures Full time

Position Overview:

We are in search of a dynamic and driven scientist with substantial expertise in computational structural biology, coupled with outstanding AI/ML computational and programming capabilities. This role is pivotal in providing strategic vision, innovative thinking, and critical insights for the advancement of novel protein-based therapies at Flagship Ventures.

The ideal candidate will possess a deep understanding of contemporary structural biology methodologies and tools, including but not limited to Rosetta, RX diffusion, AlphaFold, and ESM Fold. They will be adept at evaluating, implementing, and testing cutting-edge platforms with proprietary data to assess their effectiveness within our organization.

A robust grasp of protein modeling, ligand-structure interactions, and protein-protein dynamics, along with knowledge in cell signaling, bioinformatics, and biochemistry, is essential.

Furthermore, the candidate should have a solid foundation in traditional AI/ML techniques (e.g., supervised and unsupervised learning) and generative models, as well as experience with cloud computing environments. Familiarity with network inference, knowledge graphs, deep learning, and generative systems using diverse biomedical datasets is highly desirable. The ability to create impactful visualizations of complex datasets using programming languages such as Python and R is crucial.

The successful candidate will lead and expand a team within a broader AI and computational framework, tackling significant technical challenges in leveraging the viral proteome through in silico algorithms. This includes predicting binding affinities between proteins, guiding the generation and evaluation of CryoEM structures, differentiating proteins based on surface characteristics, applying physics-based methods to refine lead candidates, and developing predictive models to assess the viability of potential viral proteins.

As a thought leader within the organization, the candidate should excel at articulating complex technical concepts to diverse audiences, focusing on strategically relevant ideas and effectively weighing their relative merits for informed decision-making. Additionally, they should proactively leverage their technical and organizational expertise to identify, organize, and initiate new internal and external initiatives that foster cross-functional collaboration and insight.

Finally, the ideal candidate will thrive in a fast-paced, intellectually stimulating environment typical of a small company. This position offers a unique opportunity to significantly impact the evolution of Flagship Ventures' computational discovery and preclinical platforms through the development of innovative strategies for biotherapeutic drug discovery.

Key Responsibilities:

  • Build, lead, and manage a team dedicated to computational structural biology and modeling within a larger computational organization that integrates insights from chemistry, biology, and data science.
  • Strategically identify, frame, prioritize, and execute projects across the entire spectrum of target discovery and preclinical testing to expedite the identification and optimization of potential viral proteins against human targets.
  • Collaborate seamlessly across knowledge graphs that incorporate external, public-domain data and novel measurements generated from internal laboratory experiments.
  • Lead internal collaborations with cross-functional partners and stakeholders, employing advanced analytical techniques to predict physiochemical properties in silico and mitigate risks in the development of protein-based therapies.
  • Stay at the forefront of structural biology, including protein folding, alignment, clustering, and ligand binding, while introducing the latest computational tools and methodologies into the Flagship Ventures ecosystem.
  • Contribute to the establishment of best practices in AI/ML and software development within Flagship Ventures, encompassing data management, cloud-based platforms, security, and version control.
  • Contribute to scientific publications and intellectual property disclosures.

Minimum Qualifications:

  • PhD in structural biology, computational biology, bioengineering, or a related field.
  • 6+ years of industry experience in drug research and development within pharma/biotech or life sciences, with prior experience in both technical and strategic leadership roles.
  • High proficiency in developing and/or implementing AI/ML models using Python and R, particularly in generative protein design, knowledge graphs, semantic modeling and inference, supervised/unsupervised learning, and large language models. Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras, MXNet) and cloud platforms is essential.
  • Demonstrated expertise in structural biophysics, particularly in protein folding, protein-protein interactions, and protein function estimation, with familiarity in tools such as AlphaFold, ESM, USalign, Rosetta, and RF Diffusion.
  • Publications in high-impact journals, conference proceedings, or widely utilized codebases.

Preferred Qualifications:

  • Experience in structural protein design, analysis, and modeling.
  • Familiarity with generative AI capabilities for lead optimization.
  • Previous experience in drug research and development in a leadership capacity.

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