"Researcher in Machine Learning for Ice Sheet Projections"

Department of Geography

The School of Global Affairs (SGA) is a dynamic hub of multi-disciplinary scholarship that seeks to address the most pressing issues facing our world today. At King’s, we are deeply committed to embedding good equality and diversity practices into all our activities so that the university is an inclusive, welcoming, and inspiring place to work and study, regardless of age, disability, gender reassignment, marital status, pregnancy and maternity, race, religion, sex, or sexual orientation. King’s offers inclusive benefits to staff, including flexible working, Enhanced Parental Leave, funds for Parents and Carers, and the potential to join community staff networks.

About the role

You will join a team of climate scientists and artificial intelligence experts to generate new projections of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles of simulations extending to 2300. The simulations will be from two international projects aiming to inform the Intergovernmental Panel on Climate Change Seventh Assessment Report (AR7): PROTECT (EU Horizon 2020), which has produced thousands of ice sheet and glacier simulations, and ISMIP7 (Ice Sheet Model Intercomparison Project for CMIP7), which will have new ice sheet simulations in 2026. You will use your emulators to make projections of the ice sheet and glacier contributions to global mean sea level to 2300, calibrate these projections with observational data, and compare the results with those from other emulators of similar datasets (e.g. Gaussian Process methods by the project lead). These results will inform the IPCC AR7, and adaptation and mitigation policymaking by other global stakeholders. You will be based in the Department of Geography and responsible to Prof Tamsin Edwards (line manager and project lead) and Dr Alex Bradley (first supervisor), working with Dr David Watson (Department of Informatics). This position is funded by King’s Climate and Sustainability. The key responsibilities of the role are to develop machine learning emulators of multiple ice sheet and glacier models, using ensembles of simulations, in collaboration with the project scientists, with the purpose of delivering projections for the land ice contribution to global mean sea level rise to 2300. This also includes: writing up this research for publication in leading international journals; disseminating research results through conference presentations; and communicating research results to relevant stakeholders. This post will be offered on a fixed term contract for 12 months from the day you start.

About you

Essential criteria

1. PhD qualified in mathematical, physical or computational sciences
2. Experience in using machine learning methods to analyse datasets
3. Experience in statistical or scientific programming (ideally R and/or Python)
4. Experience in analyzing large and/or complex datasets
5. Interest in quantifying uncertainties for computer models and/or climate predictions
6. Ability to work in a team
7. Ability to communicate orally in English
8. Ability to write clearly in English

Desirable criteria

1. Knowledge about sea level rise or polar climate change
2. Experience in working with data from ice sheet, glacier or climate models
3. Experience working in a multi-disciplinary team