Ben Moseley

No summary provided for this position.

The Scalable Scientific Machine Learning Lab at Imperial College London, led by Assistant Professor Ben Moseley, is recruiting several PhD students for projects starting September 2026. Research topics include multi-scale simulation with physics-informed neural networks, brain ultrasound imaging using diffusion-guided full-waveform inversion, climate modeling with neural differential equations, and learning dynamics on manifolds with neural geodesic flows. The lab also welcomes new project proposals related to scientific machine learning. These positions are eligible for Imperial PhD scholarships, which are open to both UK and international students and typically cover tuition and provide a stipend. Applicants should have a strong background in computer science, mathematics, physics, engineering, or related fields, and experience in machine learning or scientific computing is highly desirable. The application process involves submitting a CV, motivation letter, and, if applicable, a research proposal. Shortlisted candidates will be invited for an interview, a coding task, and a short research talk. The deadline for most scholarship applications is early January 2025. For full details and application instructions, visit the lab website or contact Dr Ben Moseley directly.

Ben Moseley, newly appointed Lecturer (Assistant Professor) at Imperial College London, is recruiting PhD students for the Scalable Scientific Machine Learning Lab. The lab focuses on developing advanced scientific machine learning (SciML) algorithms to accelerate scientific discovery, with applications in Earth science, space science, and related fields. The position is based in the Department of Earth Science and Engineering at Imperial College London, a leading UK institution. Ben Moseley also holds a Schmidt AI in Science Fellowship at the Imperial I-X Centre, fostering collaboration with a vibrant research community. Candidates interested in AI, machine learning, scientific computing, Earth science, or space science are encouraged to apply. While specific eligibility criteria and funding details are not provided in the post, applicants should have a strong background in computer science, mathematics, physics, or related disciplines. For more information and application instructions, candidates should visit benmoseley.blog and monitor the upcoming lab website. This is an exciting opportunity to join a new research group at a world-class university and contribute to cutting-edge scientific research.

Ben Moseley, newly appointed Lecturer (Assistant Professor) at Imperial College London, is leading the Scalable Scientific Machine Learning Lab in the Department of Earth Science and Engineering. The lab focuses on accelerating scientific discovery by developing advanced scientific machine learning (SciML) algorithms and applying them to Earth science, space science, and related fields. Ben is also a Schmidt AI in Science Fellow at the Imperial I-X Centre. The lab is currently recruiting PhD students interested in scientific machine learning, AI, Earth science, and space science. Applicants should have a strong background in computer science, mathematics, physics, or related disciplines. Funding details and specific requirements are not provided in the post; candidates are encouraged to visit benmoseley.blog for more information and application instructions. The lab website will be launched soon. This opportunity is ideal for students passionate about pushing the boundaries of scientific research with AI at a world-leading institution.