During autumn 2019, eSSENCE@UU invited for Letters of Interest to identify 2-year post-doctoral projects focussing on new e-Science methods and tools within the field of AI for the sciences. Seven projects have now been prioritized and will be supported by eSSENCE. The titles of the projects, including links to the announcements of the positions, are found below:
- Federated learning to solve the data-sharing problem in radiation treatment planning
- AI tools to identify individuals with high risk of developing a common disease
- Explainable AI for e-Science
- Misclassification and out-of-distribution sample detection and handling in bio-medical deep learning classification problems
- Automated, AI-guided laboratory in drug discovery
- Domain-Sensitive Cross-Lingual Parsing
- Decision Making with Limited Data using Artificial Intelligence – An Active Inference Approach
This eSSENCE initiative is connected to the new cross-disciplinary effort AI4Research at Uppsala University, with the aim to specifically support this effort by research on new e-Science methods and tools within AI to provide a foundation for the future development of the field.