Ten new fellows have joined the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship programme at the University of Oxford, two of whom will be joining the Department of Physics. In October 2022 the University of Oxford became one of nine leading research universities around the world selected to deliver the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship programme. The Department of Physics welcomed three of the ten fellows recruited to Oxford in 2023 and a further five fellows last year.
The Schmidt AI in Science Postdoctoral Fellowship, a programme of Schmidt Sciences, aims to accelerate the next scientific revolution by applying artificial intelligence (AI) techniques to research across the natural sciences, engineering, and mathematical sciences.
Meet the Physics fellows:
- Deaglan Bartlett, Department of Physics – Trustworthy machine learning for cosmological discovery
- Hattie Stewart, Department of Physics – Galaxy modelling in next-generation radio surveys with machine learning
Eight other Schmidt AI in Science Postdoctoral Fellows will be joining the University of Oxford:
- Alycia Leonard, Department of Engineering Science – Predicting empowerment: AI-driven targeting of best-fit energy services for efficient sustainable development
- Taniya Kapoor, Department of Engineering Science – Engineering-informed foundation models for sustainable bridges
- Thomas Monahan, Department of Engineering Science – Global operational storm surge prediction using scientific machine learning and satellite altimetry
- Daniel Schofield, Department of Engineering Science – Scaling AI for ethology and wildlife conservation: towards automated monitoring of primates in the wild
- Augustin Marignier, Department of Earth Sciences – Illuminating the Earth’s inner core with Bayesian machine learning
- Jonathan Pattrick, Department of Biology – Characterising pollinator energetics and foraging strategies using machine learning
- Yuxing Zhou, Department of Chemistry – Understanding amorphous oxides for solar cell applications using generative machine learning
- Jiahe Cui, Department of Engineering Science – AI-enabled understanding of oculomotor control throughhigh resolution imaging of the human retina