The PhD programme addresses the translation of research results to clinical adaptation and commercial outcomes in three research areas of precision medicine concerning epilepsy, traumatic brain injuries and neurodegenerative diseases, which have a long history as particularly strong, internationally top ranked research areas of UEF neuroscience.
- Societal impact of prediction and early diagnosis research area aims to understand and improve interdisciplinary, societally impactful research collaborations on novel biomarkers and risk genes, key mechanisms of epilepsy/TBI and neurodegenerative diseases, and the effect of environmental factors on brain health. To accelerate prediction and early diagnosis, sophisticated machine learning prediction tools will be used and integrated with high-level legal and social science expertise on patient rights, public health ethics and inclusivity to society. Interdisciplinary impact and innovation management processes will be studied from a holistic perspective.
- Co-innovation for prevention and treatment research area deals with collaborative innovation across networks and ecosystems where novel therapies are developed, tested, and launched for the purpose of preventing and treating neurodegenerative diseases and epilepsy. Together with the key intersectoral partners, the research will focus on new drug candidates, multi-domain lifestyle-based interventions, and personalized clinical treatments. For high-level outcomes, machine learning will be used to identify patient groups for specific treatments and predict therapy response. Intersectoral co-innovation processes will be studied, and research designs will be guided by legal expertise on law and medical ethics.
- Transfer of technologies, methods, and models research area aims to understand and improve knowledge transfer processes across research teams and from university to industry. This research area deals with new technologies, such as experimental MRI techniques and multiscale imaging. Novel methods and models include cohorts and population-based trials, use of human brain tissue samples, genetically modified animal models and human-based disease models. Sophisticated algorithms and competence on inverse problems will be utilized, together with legal expertise on privacy, data protection and data sharing policies. Entrepreneurial processes will be studied to achieve success in research commercialization.
More specific research topics will be outlined in the call and on this website.