"Postdoctoral Research Associate or Fellow"

We are seeking to appoint a Research Fellow or Research Associate to join one of five QCF projects in the rapidly expanding area of solar radiation modification. The main objective of the research will be to apply state-of-the-art statistical and machine learning methods to the United Kingdom Earth System Model (UKESM1) to explore the potential climate impacts of marine cloud brightening (MCB). The University of Exeter performs cutting-edge world-leading research into SRM under the Global Systems Institute (https://www.exeter.ac.uk/research/institutes/gsi/research/rci/) and in the aerosols cloud and climate group (https://www.exeter.ac.uk/research/groups/aerosol-clouds/).

Uncertainties surrounding the representation of complex, non-linear cloud processes (e.g., cloud droplet activation) by simplified parameterisations propagate to climate modelling of MCB impacts. Only a limited number of MCB deployment strategies have been investigated using climate models (e.g., location, timing, size and amount of aerosol), and a large fraction of the possible scenario parameter space still remains unexplored, preventing a robust examination of the potential climate impacts.

The post holder will work on constructing an exceptionally fast and accurate surrogate model using modern-day statistical and machine learning methods of the UKESM1 to understand how different MCB injection strategies impact the climate system. The successful candidate will explore various strategies such as inverse problem methods, Bayesian calibration as well as history matching to examine these impacts.

As part of this project, the post holder will apply these statistical techniques to the UKESM1 and recently developed parameterisations of cloud droplet activation developed within Dr Patridge's research group. The post holder will gain invaluable experience in climate modelling, and the topic of aerosol–cloud–interactions, which remain as the largest uncertainty in the human forcing of the climate system. The role will involve working closely with other QCF team members and opportunity for collaboration with staff in the Department of Mathematics and Statistics working in uncertainty quantification (https://www.exeter.ac.uk/research/institutes/idsai/research/uncertaintyquantification/).

Candidates should have experience in constructing surrogate models for complex computer models such as Gaussian Processes and/or Deep Learning models, advanced regression models; and/or various inverse problem techniques such as Bayesian calibration and history matching. Candidates should have experience in atmospheric science or climate and an interest in modelling aerosol-cloud-interaction processes.

The University of Exeter is an equal opportunity employer. We are officially recognised as a Disability Confident employer and an Athena Swan accredited institution. Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented in the workforce.

We offer some fantastic benefits including: 39/41 days leave per year, options for flexible working, numerous discounts at leading retailers, onsite gyms on all of our campuses and a cycle to work scheme, sector leading policies around maternity, adoption and shared parental leave (up to 26 weeks full pay), paternity leave (up to 6 weeks full pay) and a Fertility Treatment Policy, stunning campus environments in Exeter and Cornwall, in the beautiful South West of England.