About the role
AI summarisedWe are seeking a PhD-level Computational Scientist to join an interdisciplinary research team focused on integrating computation, AI/ML, and drug discovery. The role involves developing novel computational methodologies to accelerate drug R&D, collaborating with domain experts, and publishing research.
ResearchFull-timeBioinformatics Institute
Key Responsibilities
- Design and deploy innovative computational approaches - integrating physics-informed, biology-informed, causal and uncertainty-aware machine learning — to accelerate and de-risk key stages of drug R&D, including target/biomarker identification, molecular optimization, translational predictive modeling.
- Develop and optimize computational frameworks that integrate diverse data types (chemical, biological, omics, clinical) into cohesive models.
- Collaborate with domain experts in computational biology, cheminformatics, pharmacology, and drug discovery to tailor computational models to real-world problems.
- Publish research findings in leading journals and conferences, and contribute to partnerships and strategic initiatives as opportunities arise.
- Mentor junior team members and contribute to a collaborative, cross-disciplinary research environment.
Requirements
- PhD in Artificial Intelligence/Computer Science, Bioinformatics, Computational Biology, Biomedical Engineering, Applied Mathematics, Pharmaceutical Sciences or a related field, with a focus on machine learning or computational modeling.
- Strong publication record or demonstrable contributions to open-source tools or reproducible research.
- Demonstrated expertise with AI/ML methodologies and implementations.
- Excellent problem-solving skills, with an ability to balance theoretical rigor with practical implementation.
- Familiarity with challenges in drug discovery and development.
- Research interest in areas of AI/ML such as Multi-Agent Systems, Physics-Informed ML, Causal AI, Neuro-Symbolic AI, Uncertainty Quantification, Active Learning, Geometric Deep Learning.