Postdoctoral Researcher in Geospatial Foundation Models for the Analysis and Compression of Atmospheric Data
University of Oxford
The post-holder will be based in the Atmospheric, Oceanic and Planetary Physics sub-department, which is one of the six sub-departments that together make up the Department of Physics; these are Astrophysics, Atomic and Laser Physics, Atmospheric, Oceanic and Planetary Physics, Condensed Matter Physics, Particle Physics and Theoretical Physics, with a seventh function (Central Physics) providing administrative and technical support to these sub- departments. AOPP’s research can be broadly categorized into climate physics and planetary research. Cross-cutting themes of planetary circulation & composition as well as cross-cutting methodologies (theory, observations, modelling, AI/ML) intrinsically link these research areas. Members of all sub-departments take part in research, teaching and matters such as examinations, discussion of syllabi, lectures and liaison with undergraduates and postgraduate students.
For more information please visit:
Climate: Past, Present & Future (CL)
Earth and Space Science Informatics (ESSI)
We are looking for an enthusiastic postdoctoral researcher in the dynamic Climate Processes Group within the sub-Department of Atmospheric, Oceanic and Planetary Physics of the Department of Physics at the University of Oxford. The post is available immediately for a fixed-term period of 36 months.
This position, part of EU Horizon Europe project Earth Observation & Weather Data Federation with AI Embeddings (Embed2Scale), with IBM and partners across Europe, will be at the forefront of tackling our understanding and compressed representations of clouds in the climate system through the development and utilisation of geospatial foundation models.
The successful candidate will work closely with IBM and our international collaborators and be expected to develop innovative approaches. The results should be presented at national and international meetings as well as published in leading subject and high-impact publications.
Applicants should possess, or be close to obtaining of a PhD / Doctorate in in atmospheric physics, physics, data sciences, AI, machine learning or related fields.
Candidates are expected to demonstrate an excellent understanding of atmospheric physics / physics or data sciences (AI, ML), with a strong interest to expand into the complementary subject area, and a demonstrated drive and ability to perform novel research of international standing.
Please direct enquiries about the role to Philip Stier (email@example.com).
You will be required to upload a supporting statement, CV and details of two referees as part of your online application. Further particulars and the application form can be found on the Oxford University recruitment webpage .
Application deadline: midday 15 January 2024