This success not only underscores the Centre's dedication to advancing its convergence mission but also emphasises our commitment to cultivating the next generation of experts in vital interdisciplinary research fields such as chemical biology, engineering, and data sciences. Through this enhanced support, we look forward to contributing significantly to these areas of critical need.

The EPSRC Institute of Chemical Biology CDT

This CDT, now in its fourth renewal with £26m funding, is hailed as a premier PhD training hub, solidifying Imperial's status as a global leader in chemical biology education and research. Directed by Dr. Laura Barter and a team of co-investigators from Imperial's Department of Chemistry, the CDT focuses on creating molecular tools and technologies to address life sciences challenges, with industrial or clinical advantages.

It highlights the CDT's ambition to foster breakthroughs in disease understanding, agrochemical design, and product development, its broad, global reach and potential to stimulate regional economic development. The training programme is a collaborative effort involving over 165 academics across 20 departments at Imperial, crafted in partnership with over 100 industry leaders in various sectors, as well as new civic partners, demonstrating a comprehensive approach to chemical biology education and innovation.

The EPSRC CDT in Statistics and Machine Learning (StatML)

Boasting renewed funding of £14m, this CDT is set to train the next wave of leaders in the fields of statistics and machine learning. This initiative aims to pioneer methodologies essential for advancing data science and AI. Spearheaded by Dr. Sarah Filippi and Dr. Ed Cohen from the Department of Mathematics, and in collaboration with the University of Oxford, this programme is enhanced by the support of various industrial and international partners. Recognising the transformative impact of data science and AI across all economic sectors, the CDT focuses on crafting new methods designed to address the looming societal challenges. The foundation of these methods lies in the integration of statistics and machine learning.

This CDT highlights the importance of this initiative, especially in light of recent disruptive advancements in AI. The training will not only equip doctoral students with advanced technical skills but also instil in them a commitment to ethical practices, reproducible research, and open science, enabling them to tackle global challenges and develop technologies with the potential to transform society.

More information: 

https://www.imperial.ac.uk/news/251995/46m-phd-boost-three-centres-doctoral/amp/ 

https://www.ukri.org/news/1-billion-doctoral-training-investment-announced/