Accelerate Science Winter School

Artificial intelligence (AI) has the potential to become an engine for scientific discovery across disciplines – from predicting the impact of climate change, to using genetic data to create new healthcare treatments, and from finding new astronomical phenomena to identifying new materials here on Earth.

To reach the full promise of this exciting methodology scientists and AI researchers need to work together. Only by creating an interface that stimulate knowledge transfer between AI and the sciences will we be able to exploit the benefits of current technology and importantly provide motivation to direct methodological development in AI from scientific questions.

With this as motivation we created the Accelerate Science Winter School with the aim of bridging the gap between early career researchers in the sciences with AI researchers. The first school will took place Virtually between the 2nd and the 4th of February, 2021. We hope to arrange further schools in the future.

Accelerate Science

The Accelerate Programme for Scientific Discovery will advance the frontiers of science through the application of AI. Supported by a donation from Schmidt Futures, a philanthropic initiative founded by Eric and Wendy Schmidt, the Accelerate Programme will provide young researchers with specialised training in AI techniques, equipping them with the skills they need to use machine learning and AI to power their research.

Based in the Department for Computer Science and Technology at the University of Cambridge, the Programme will build an interdisciplinary community of researchers working across the University at the interface of machine learning and the sciences. Our work spans:

Accelerate Science pursues research that applies machine learning to the scientific challenges of the 21st century, generating insights that accelerate scientific progress and creating AI tools that are capable of delivering benefits for science and society.
Education and training
Through a range of learning and development activities, Accelerate Science is equipping early career researchers and future research leaders with the data science and machine learning skills that will enable them to drive a new wave of scientific progress
Accelerate Science will build a community of committed researchers to promote and facilitate the use of machine learning techniques across research domains, with the aim of sharing best practice and building research collaborations that can accelerate the process of scientific discovery.



Speaker Winter 2021


Jessica Montgomery

Executive Director, Accelerate Program for Scientific Discovery


Neil D. Lawrence

Professor Machine Learning


Andreas Damianou

Senior Scientist


Alessandra Tosi

Senior Research Scientist


Yang-Hui He

Professor in Mathematics


Javier Gonazales

Principal Research in Machine Learning


Challenger Mishra

DECAF Fellow


Aleksandrina Goeva

Postdoctoral Fellow


Vishnu Jejjala

Chair: Theoretical Particle Cosmology


Jim Halverson

Assistant Professor of Physics


Markus Kaiser

Postdoctoral Researcher Machine Learning


Carl Henrik Ek

Senior Lecturer Machine Learning