Research Associate in Atmospheric Dynamics

About the role

Join a major new research programme investigating how atmospheric gravity waves shape the Earth’s atmosphere, weather & climate. You will study how these waves transport energy and momentum, and help improve how they are represented in weather and climate models.

You will work within an international team combining satellite observations, ground-based measurements, & high-resolution numerical simulations. You will also apply machine learning and advanced computational intelligence (ML/AI) methods to address the longstanding “observational filter problem.” Our goal is to produce physically-consistent measurements of global atmospheric wave activity.

For context on our group’s work, see our 2022 multi-instrument gravity wave paper in Nature, which introduced some of the observational techniques that underpin this research, and our recent press release on our involvement in developing new satellite observations.

As a member of Bath's research staff, you will be entitled to at least 10 days’ professional development each year and will have freedom to shape your own science within the broad goals of the research. We actively support postdoctoral researchers in developing independent research directions & fellowship applications, and recent members of the group have progressed to lectureships, independent research fellowships, and positions in meteorological agencies, industry and academia.

About you

We are looking for someone who:

• Is enthusiastic about understanding how the atmosphere works and solving challenging scientific problems.
• Has, or is close to completing, a PhD in atmospheric science, physics, meteorology, mathematics or a related field.
• Has experience analysing scientific data & developing research software.
• Is interested in applying machine learning and artificial intelligence techniques to atmospheric observations 
• Enjoys working collaboratively & communicating science to a range of audiences.
• Is motivated to publish high-quality research and develop an international research profile.

The successful candidate will:

• Investigate how atmospheric gravity waves are generated, propagate through the atmosphere and influence the large-scale atmospheric circulation.
• Analyse observations from NASA and ESA satellites alongside ground-based measurements and high-resolution atmospheric simulations.
• Learn and apply ML/AI methods to combine complementary measurements and recover aspects of the gravity wave field that cannot currently be observed systematically.
• Use the resulting measurements to help develop, apply and evaluate a new gravity wave parameterisation for the Whole Atmosphere Community Climate Model (WACCM), working with colleagues at Bath, the British Antarctic Survey and the US National Center for Atmospheric Research.
• Publish in high-impact journals, present at international conferences, and contribute to open-source scientific software and datasets.

Previous experience of ML/AI is not required, as the post includes dedicated training in this domain. We therefore primarily seek applicants with relevant scientific expertise and strong quantitative or computational skills who are interested in applying new methods to an important atmospheric science problem. Other skills will be fairly considered where they would contribute significantly to our team.

The research spans a broad range of techniques, and we are keen to build on the successful candidate’s existing strengths. We would particularly welcome applicants with experience in satellite retrievals or remote sensing, atmospheric dynamics and wave theory, high-resolution atmospheric modelling, or the development and evaluation of atmospheric parameterisations. We also welcome applicants from complementary scientific backgrounds who can demonstrate how their expertise would contribute to the aims of the research.

Further information

This is a full-time (36.5 hours per week) fixed-term role with an expected end date of 30/09/2029.

For an informal discussion regarding the role, please contact Juli Jaen at jmj70@bath.ac.uk

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