Postdoctoral Researcher in Clouds, Aerosols & Climate using Machine Learning
University of Oxford
About the University of Oxford
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Department of Physics
Oxford Physics is one of the largest and most eminent departments in Europe – pursuing forefront research alongside training the next generation of leaders in Physics.
With an academic staff of almost one hundred our activities range from fundamental particles to the furthest reaches of the universe to manipulating matter on an atomic scale. Oxford physicists are probing new ways to harness solar energy, modelling the Earth’s atmosphere to predict the future climate, exploring computation on the quantum scale and executing calculations that reveal the fundamental structure of space and time.
For more information please visit: http://www2.physics.ox.ac.uk/
Atmospheric, Oceanic and Planetary Physics Sub-department
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) 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: https://www2.physics.ox.ac.uk/research/atmospheric-oceanic-and-planetary-physics
Climate: Past, Present & Future (CL)
Geosciences Instrumentation and Data Systems (GI)
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 3 years.
The focus of this project will be to develop novel machine-learning based constraints on clouds, aerosols, their interactions and feedbacks, combining remote-sensing and in-situ observations, high-resolution and climate modelling with modern machine learning approaches.
This position will be part of the ERC project “Constraining the effects of aerosols on precipitation” (RECAP) and the EU H2020 collaborative project “Constrained aerosol forcing for improved climate projections” (FORCeS).
The successful candidate will work closely with international collaborators and be expected to develop innovative approaches. The results should be presented at national and international meetings as well as published in high-impact publications. Applicants should hold a doctorate/PhD (or be close to completion) in atmospheric/climate physics, machine learning or related fields, and have a strong background in either atmospheric physics or machine learning (with a demonstrable interest or experience in the other field).
Please direct enquiries about the role to Philip Stier <firstname.lastname@example.org>.
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.
Only electronic applications received through this form before the deadline of 12.00 midday on 15 February 2021 can be considered.