Led by Dr Pedro Goncalves, it will provide hands-on experience to discover how biological principles and deep learning can combine to provide ever better performance.

This workshop introduces PhDs and PostDocs interested in computational modeling to recent advances in probabilistic deep learning. Computational modeling is essential for hypothesis generation and testing in natural sciences.  However, connecting model predictions to data, a process that is known as statistical inference, can be challenging. Simulation-based inference (SBI) addresses the challenge of relating models to empirical data. This workshop introduces deep-learning based SBI tools and their application in order to equip scientists to solve challenging research problems.

PhDs and PostDocs from any scientific discipline with basic Python skills are invited to apply. 

Apply for a place by 29 February 2024.