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 AI
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 social policy interventions
- Taniya Kapoor, Department of Engineering Science – Engineering-informed foundation models for sustainable materials discovery
- Thomas Monahan, Department of Engineering Science – Global operational storm surge prediction using neural differential equations
- Daniel Schofield, Department of Engineering Science – Scaling AI for ethology and wildlife conservation
- Augustin Marignier, Department of Earth Sciences – Illuminating the Earth’s inner core with Bayesian AI
- Jonathan Pattrick, Department of Biology – Characterising pollinator energetics and foraging dynamics using computer vision and AI
- Yuxing Zhou, Department of Chemistry – Understanding amorphous oxides for solar cell design using AI-driven modelling
- Siyi Yang, Department of Materials – Automated crystal growth parameter exploration using autonomous agents