Workshop: Simulations to Solutions: AI, FAIR Data, and Sustainable Scientific Careers

Recent breakthroughs in generative AI and protein modeling now allow scientists to move across the full sequence–structure–function landscape—capturing not only static folds, but also molecular motion, resistance mutations, and drug-binding pathways.

By connecting AI-driven modeling with FAIR molecular-simulation resources, the workshop will open space for lively discussion and highlight real-world applications in:

1. Antimicrobials: using AI to uncover new ways to outsmart resistance and design antibiotics with novel modes of action.

2. Metabolomics: linking protein dynamics to metabolic networks to reveal vulnerabilities, biomarkers, and new therapeutic strategies.

3 . Environmental health: designing enzymes for bioremediation, from plastic degradation to PFAS remediation, and predicting how pollutants interact with biological systems.

Alongside the technical program, an open-discussion afternoon dedicated to Women in Science (WINS) will focus on the human side of research. The session will explore how growing global competition shapes scientific careers, how these pressures are experienced differently across communities and career stages, and how experimental and data-driven cultures are blending in modern laboratories.

The workshop invites the community to help build a future where FAIR data and responsible AI deliver better medicines and cleaner environments, while also supporting inclusive, resilient, and fulfilling scientific careers.

Deadline for poster abstract submissions is April 26, 2026.