Centre for the Mathematics of Planet Earth at the University of Reading

Doctoral Training in the Mathematics for our Future Climate: Theory, Data and Simulation

Be at the forefront of mathematical solutions for climate challenges!

The University of Reading, the University of Southampton, and Imperial College London are thrilled to invite passionate and dedicated individuals to apply for fully funded PhD studentships with the EPSRC CDT in the Mathematics for our Future Climate, a dynamic and interdisciplinary PhD programme that harnesses the power of mathematics to address the urgent issues presented by climate change.

Visit https://www.reading.ac.uk/maths-and-stats/phd/mathematics-for-our-future-climate for further information on the programme.

Apply as early as possible! Applications will be open until all places are filled.

EPSRC Centre for Doctoral Training in the Mathematics for our Future Climate – Department of Mathematics and Statistics, University of Reading Apply now for our Mathematics for our Future Climate Centre for Doctoral Training (MFC CDT) PhD programme to address climate change.

CMPE authors: Reconstruction of source terms in transport-diffusion and Navier-Stokes equations.

Reconstruction of wide spectrum forcing in transport-diffusion and Navier-Stokes equations This article considers the problem of reconstructing unknown driving forces based on incomplete knowledge of the system and its state. This is studied in both a linear and nonlinear setting that is paradigmatic in geophysical fluid dynamics and various applications. Two algorithms are proposed to ad...

Still PhD opportunities in data assimilation, machine learning, and
predictability at the University of Reading as part of our Centre for Doctoral Training in the Mathematics of Our Future Climate (MFCCDT).

Fully funded 4-year PhD studentship, starting Autumn 2025, international applicants WELCOME! Interested? Apply as soon as possible!

https://www.reading.ac.uk/.../mathematics-for-our-future...

Projects with CMPE involvement:
* Machine Learning Approaches in Bayesian and Ensemble Data Assimilation
* Data Assimilation of atmospheric and marine tracers
* Artificial Intelligence based forecasts
* Detecting synergies in climate models