Topic: AI drug discovery

Implement and optimise machine-learning systems for AI-driven drug discovery. Collaborate with research scientists on model development, distributed training, inference and evaluation, including architectures such as transformers, graph neural networks and diffusion models. The role combines experimental research with reliable engineering tools and full model-lifecycle work. Apply through the employer’s current vacancy; no fixed closing date is stated.

Lead computational chemistry contributions to drug programmes from early discovery towards candidate selection. Combine structure-based and ligand-based design with AI predictions, work closely with machine-learning scientists and experimental teams, and guide external research activities. The role includes scientific leadership and mentoring. The employer’s exact vacancy is currently accepting applications without a stated fixed deadline.