[Job Summary]
We are seeking a mid-level Structural Bioinformatician to drive the 3D characterization and optimization of our antibody drug candidates. While our NGS team identifies promising sequences, you will be responsible for modeling their 3D architectures, predicting binding affinities, and evaluating their "developability" through the lens of structural physics and AI. You will be a key player in a fast-paced startup environment, turning static sequences into dynamic, functional models.

[Key Responsibilities]
• Structural Modeling: Utilize state-of-the-art AI tools (e.g., AlphaFold-multimer, ESMFold) and traditional homology modeling to predict the structures of novel antibody-antigen complexes.
• Docking & Interaction Analysis: Perform protein-protein docking simulations to map epitopes and paratopes, identifying the key residues driving binding affinity and specificity.
• In Silico Developability: Conduct property analysis to identify structural liabilities such as aggregation “hotspots,” low stability, or poor solubility that could hinder manufacturing.
• AI-Driven Design: Stay at the forefront of generative AI for protein design (e.g., RFdiffusion, ProteinMPNN) to suggest sequence optimizations that improve candidate performance.
• Strategic Literature Surveys: Actively scout academic journals and biotech whitepapers for the latest breakthroughs in structural proteomics and ML-based folding to keep our pipeline competitive.
• Cross-Functional Collaboration: Translate complex 3D data into clear, visual insights for wet-lab scientists and stakeholders to guide lead selection.

[Remote & Multinational Team]
We operate as a fully remote organization, enabling us to recruit the best talent globally. We prioritize flexibility, trust, and output over physical location.