This PhD project at the University of Edinburgh's School of Informatics focuses on the development and validation of homecage behavioural biomarkers to enhance the preclinical translation of drug research in laboratory rodents. Preclinical drug development, especially for central nervous system (CNS) disorders, relies heavily on animal models. However, translating findings from these models to clinical success remains a significant challenge. This research aims to address this gap by leveraging advanced bioinformatics, artificial intelligence, and machine learning techniques to identify and validate behavioural biomarkers that can improve the predictive power of preclinical studies. The successful candidate will work at the intersection of neuroscience, biology, and computer science, applying computational methods to large-scale behavioural data collected from rodents in homecage environments. The project will involve designing and implementing algorithms for behavioural analysis, integrating multi-modal data, and validating findings in collaboration with experimental researchers. The ultimate goal is to develop robust, translatable biomarkers that can inform drug development pipelines and reduce the attrition rate of CNS therapeutics. The position is supervised by Professor D Armstrong, an expert in the field, and is based at the University of Edinburgh, a leading institution in informatics and biomedical research. The project offers an excellent opportunity to gain interdisciplinary skills in computational neuroscience, bioinformatics, and translational medicine. While funding details are not specified, applicants are encouraged to check the university's website for potential scholarships or funding opportunities. Applicants should have a strong academic background in a relevant discipline such as neuroscience, biology, computer science, or bioinformatics, with experience or interest in AI and machine learning. Proficiency in programming and data analysis is highly desirable. The application deadline is 20 January 2026. Interested candidates should prepare their application materials and apply online via the University of Edinburgh portal. For further information, refer to the project link or contact the supervisor directly.