Material informatics scientist

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7esytl

Questa posizione è in R2 A Labs About the role We are looking for a Materials Informatics Scientist to sit at the centre of our discovery loop, converting chemical and physical modification strategies into digital workflows, and ensuring that simulation outputs and model behaviour translate faithfully into experimental decisions. Responsibilities Build and maintain molecular dynamics (MD) and DFT workflows that translate chemical and physical modification strategies into robust data pipelines. Design and implement evaluation frameworks for computational models, defining metrics that capture generalisation, robustness, uncertainty, and experimental relevance, and assessing trade-offs between accuracy, data efficiency, and usability. Close the loop between models and experiments: connect simulation outputs to validation results, identify and investigate discrepancies, and provide clear, actionable guidance to the lab team. Develop robust analysis pipelines and benchmarking tools; visualise high-dimensional results in ways that surface real insight rather than confirm assumptions.



Interface closely with the experimental programme, identifying which data is most informative for model updates and ensuring learning compounds across iterations. Actively shape data pipelines and analytical tools through hands‐on use, ensuring infrastructure evolves in line with real scientific workflows. Qualifications Ph D (strongly preferred) or Master's (with 2+ years post‐degree experience) in computational chemistry, materials science, physics, or a closely related field with demonstrated experience in simulation‐driven projects. Hands‐on experience with MD simulations combined with working knowledge of DFT workflows. Strong Python skills and a track record of writing clean, modular, maintainable scientific code; experience with MD analysis libraries, and cheminformatics tooling (RDKit, pymatgen, ASE). Demonstrated ability to evaluate and benchmark models rigorously, with a deep apprec

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/7esytl