£41,344 - £45,479 – the band minimum is the normal starting pay for those new to a role. In exceptional circumstances, when relevant skills and experience can be identified, a higher starting salary may be considered.
Interview date – Week beginning Monday 27 January 2025
British Antarctic Survey (BAS) is looking for an exceptional Climate Modeller using Machine-Learning (ML) approaches to join our Atmosphere Ice and Climate (AIC) team. BAS delivers and enables world-leading interdisciplinary research in the Polar Regions. We employ experts from many different professions to carry out our Science as well as keep the lights on, feed the research and support teams and keep everyone safe!
Working at BAS is rewarding. Our skilled science, operational and support staff based in Cambridge, Antarctica and the Arctic, work together to deliver research that uses the Polar Regions to advance our understanding of Earth as a sustainable planet. Through our extensive logistic capability and know how BAS facilitates access for the British and international science community to the UK polar research operation. Numerous national and international collaborations, combined with an excellent infrastructure help sustain a world leading position for the UK in Antarctic affairs. British Antarctic Survey is a component of the Natural Environment Research Council (NERC), which is part of UK Research and Innovation www.ukri.org.
As a valued member of our team, you’ll be eligible for the following benefits:
- 30 days annual leave plus bank holidays and 2.5 privilege days.
- Excellent civil service pension (with 26% or more employer contribution, depending on your band).
- 24 hours/365 days access to employee assistance programme (EAP – including support with physical, mental, social, health and financial issues).
- Flexible and family friendly working opportunities.
- Cycle to work scheme.
- Access to discounted shopping on a range of retail, leisure and lifestyle categories and much more.
You’ll be joining our AIC team, consisting of scientists using models and observations to investigate the polar atmosphere-ocean-ice system, to work on Drivers and Impacts of EXTreme Weather Events in ANTarctica (ExtAnt). This project will provide the first comprehensive assessment of present day and future high impact extreme weather events in Antarctica, and associated risks. Key risks include impacts of extreme weather on vulnerable ice shelves, the breakup of which can speed up flow of grounded ice and affect global sea level, and on the highly specialised Antarctic biodiversity. This ambitious programme brings together leading UK and international scientists to use new modelling resources and methods to elucidate drivers of extreme events.
You’ll help us to deliver the BAS contribution to this work, which will mainly focus on using ML approaches to develop emulators for regional climate models (RCMs) and use them to downscale 21st century climate change projections from a subset of global climate models (GCMs) used in large-ensemble datasets and assess how high impact extreme events will change in the future, with a particular focus on the impacts on ice shelves.
Within the role, there will be an opportunity to develop your teamwork skills as you collaborate with partners across the ExtAnt consortium, which involves scientists from BAS and the Universities of Birmingham, Reading, Leeds, and Cardiff, as well as internationally. You will be able to benefit from the many training and development opportunities that UKRI and BAS have to offer.
Current projects the team are working on include PICANTE (Processes, Impacts, and Changes of ANTarctic Extreme Weather), PolarRES (Polar Regions in the Earth System; https://polarres.eu), Antarctic-CORDEX (COrdinated Regional Downscaling EXperiment; https://climate-cryosphere.org/antarctic-cordex/), SURFEIT (Surface Fluxes in Antarctica; https://surfeit.ac.uk), and HEPPI-ML (HEavy Precipitation forecast Postprocessing for India with Machine-Learning). PICANTE is a second UK led project investigating Antarctic extreme events and their impacts, and therefore has a lot of synergies with ExtAnt. PolarRES and Antarctic CORDEX focus on producing state-of-the-art RCM simulations for the Antarctic, which we will use here and develop ML-based emulators for. SURFEIT uses ML-based techniques to create RCM-emulators to downscale surface mass balance output from GCM projections over Antarctica, and therefore also has a lot of synergies with ExtAnt. HEPPI-ML also uses ML-based approaches but focuses on improving forecasts of precipitation.
You’ll be joining a world-leading interdisciplinary research organisation, that is committed to recruiting talented people like you, progressing your career and giving you the support, you need to thrive at BAS.
Some of your main responsibilities will include:
- Develop emulators of outputs from state-of-the-art RCM simulations of Antarctica using Machine-Learning (ML). Compare results with RCM-emulators based on classical statistical techniques.
- Evaluate the ability of global climate models (GCMs) used in large-ensemble datasets to represent the large-scale drivers/precursors of Antarctic extreme events for the historical period, and identify a subset of GCMs based on this analysis that are best able to represent these features.
- Use the ML-based RCM-emulator to downscale the subset of GCM models identified to develop a comprehensive ensemble of RCM outputs for a large number of GCM/RCM combinations for both the past and future climate.
- Use the comprehensive ensemble of RCM outputs to examine high-impact extreme events for both the historical and 21st century periods, and assess uncertainty estimates based on differences between the GCM/RCM combinations.
- Lead the writing of high-impact scientific research papers on the findings.
Please download job description for more details.
For the role of ExtAnt Climate Modeller using Machine-Learning approaches, we are looking for somebody who has:
- PhD in atmospheric science, geoscience, statistics, Machine-Learning, or another relevant subject.
- Experience analysing and visualizing climate model datasets.
- Strong understanding of statistics or ML techniques (e.g., deep learning approaches like convolutional neural networks (CNN), or supervised learning algorithms like random forests).
- Good understanding of climate/meteorology.
- Excellent written and oral communication skills. Fluent in written and spoken English language.
Please download job description for more details.
If we’ve just described you, we’d love to hear from you. Apply now at bas.ac.uk/vacancies.
What experiences can we offer you?
At BAS we believe everyone plays a vital role, is unique and valued, therefore, we embrace diversity as well as equality of opportunity and are committed to creating an inclusive and welcoming working environment where everyone’s unique perspectives are valued.
Different perspectives and collaborative working help us achieve our best work and come together to form a high performing team which makes positive changes in the business. That’s the power of every individual. Our cultural values are built on mutual respect, inclusion, commitment and excellence.
If you are looking for an opportunity to work with world class and amazing people in one of the most unique places in the world, then British Antarctic Survey could be for you.
If you require the job information in an alternative format (i.e. email, audio or video), or would like any further information or support, please do not hesitate to get in touch at jobs@bas.ac.uk or alternatively you can call us on 01223 221508.