Climate modeller using Machine-Learning approaches

British Antarctic Surve; Cambridgeshire and Peterborough; On-site; GBP 41,000 - 46,000; Full time

Job summary

An established industry player in climate research is seeking a talented Climate Modeller with expertise in Machine Learning. This exciting role involves developing emulators for regional climate models and analyzing extreme weather events in Antarctica. You will collaborate with leading scientists and contribute to groundbreaking research that assesses the impacts of climate change. The position offers a supportive environment with excellent benefits, including generous leave and a strong pension scheme. If you are passionate about climate science and eager to make a difference, this opportunity is perfect for you.

Benefits

30 days annual leave

Excellent civil service pension

Employee assistance programme

Flexible working opportunities

Cycle to work scheme

Discounted shopping access

Qualifications

• PhD in a relevant field and experience in climate model datasets.
• Strong understanding of ML techniques and statistics.

Responsibilities

• Develop emulators using ML for climate models of Antarctica.
• Evaluate global climate models for extreme event representation.
• Lead writing of high-impact scientific research papers.

Skills

Machine Learning

Climate Modelling

Statistical Analysis

Data Visualization

Deep Learning

Communication Skills

Education

PhD in Atmospheric Science

PhD in Geoscience

PhD in Statistics

PhD in Machine Learning

Job description

£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.

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.

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.

Some of your main responsibilities will include:

• Develop emulators of outputs from state-of-the-art RCM simulations of Antarctica using Machine-Learning (ML).
• Evaluate the ability of global climate models (GCMs) used in large-ensemble datasets to represent the large-scale drivers/precursors of Antarctic extreme events.
• Use the ML-based RCM-emulator to downscale the subset of GCM models identified to develop a comprehensive ensemble of RCM outputs 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.
• Lead the writing of high-impact scientific research papers on the findings.

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.

If we’ve just described you, we’d love to hear from you. Apply now at bas.ac.uk/vacancies.

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.

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 [e-mail] or alternatively you can call us on 01223 221508.