Join Us to Build the Next Generation of Structural Biology AI Immuto Scientific is on a mission to transform drug discovery by unlocking the hidden structural biology of human disease. We are building a proprietary AI platform that learns directly from experimental data generated on real biological systemspatient samples, tumor models, and complex protein assembliesrevealing in vivo protein conformations that existing approaches cannot access. At the core of this effort is Immutos unique experimental platform, which combines radical labeling chemistries with LC/MS peptide mapping and structural analysis to generate novel, information-rich structural datasets. These datasets form the foundation of our AI/ML systems and enable structure-informed target discovery and therapeutic development in ways that go beyond current computational-only models. This is a rare opportunity to play a foundational experimental role in an AI-driven structural biology platform. As the scientist responsible for generating ML training data, you will work in tight collaboration with our machine learning team to design, execute, and iterate on experiments that directly shape how our models learn and improve. Your work will not only support customer projects, but also help pioneer a new frontier at the intersection of structural proteomics, artificial intelligence, and precision medicine.What Youll Do Own the wet-lab side of experimental R&D for machine-learning training data, working closely with AI scientists to translate modeling goals and data needs into well-designed, iterative experiments Learn and run Immutos proprietary radical labeling and LC/MS peptide-mapping platform across the full workflow, from sample preparation through data generation Design, execute, and analyze experiments end-to-end, including reagent selection and quantities, automation and liquid-handler setup, LC/MS operation, mass-spectrometry data analysis, custom R-based pipelines, and interpretation of results in the context of structural biology and ML requirements Curate, format, document, and transfer high-quality, ML-ready datasets, iterating experimentally based on model feedback to improve data quality and usefulness Research, source, and procure protein and biomolecular reagents; manage inventory, procurement, and experimental readiness Support customer projects in parallel with internal AI-driven R&D, generating and analyzing experimental data and communicating results to internal stakeholdersWho You AreRequired Qualifications PhD (or MS with significant industry experience) in Biochemistry, Analytical Chemistry, Chemical Biology, Structural Biology, or a related field Strong hands-on experience with LC/MS-based protein or proteomics workflows Demonstrated ability to independently design, execute, and iterate on complex experiments Comfort owning projects end-to-end in a fast-moving, ambiguous startup environment Excellent communication skills and ability to collaborate deeply across wet-lab and computational teams Strong organizational and project-management skillsPreferred Qualifications Experience with one or more of:o Hydroxyl radical protein footprinting (HRF) o HDX-MS, XL-MS, or related structural MS techniques Experience with laboratory automation and liquid handlers Proficiency in R (or similar) for data analysis and visualization Familiarity with protein structure, conformational dynamics, or antibody-antigen systems Industry experience in drug discovery, biologics, or structural biology
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