A fully funded postdoctoral opportunity is available in computational chemistry and drug discovery, jointly hosted by the Barcelona Supercomputing Center (Spain) and RMIT University (Australia) as part of the Australia-Spain Network for Innovation and Research Excellence (AuSpire). The position focuses on combining machine learning algorithms with molecular modelling approaches to identify entities that modulate complex protein-protein interactions, a key challenge in modern drug discovery.

The successful candidate will work on large computational infrastructure and interact with major pharmaceutical companies. The research will involve developing and applying AI and molecular modelling techniques for hit identification in drug discovery, leveraging the resources and expertise of both host institutions. The position includes a 1-year secondment at RMIT University, providing international collaboration and exposure to cutting-edge research environments.

Applicants should have a PhD in chemistry, computational chemistry, molecular modelling, computer science, or a related discipline. Experience with machine learning, molecular modelling, and drug discovery is highly desirable, along with strong programming skills and familiarity with large-scale computational resources. The position is fully funded for three years, covering salary and research expenses.

Applications are open until January 26, 2026. Interested candidates should review the full position description and submit their application via the official Auspire portal. For further information, contact Professor Victor Guallar at the Barcelona Supercomputing Center.

Keywords: Computational Chemistry, Drug Discovery, Molecular Modelling, Machine Learning, Protein-Protein Interactions, AI Modelling, Large Computational Infrastructure.