Postdoctoral Researcher in Machine Learning for Exoplanet Atmospheric Modelling

TL;DR

Postdoctoral Researcher (Machine Learning for Exoplanet Atmospheric Modelling): Developing a neural network-based emulator for Mie scattering calculations, integrating it into the NemesisPy atmospheric model with an accent on applying to James Webb Space Telescope observational data to constrain hot Jupiter cloud composition. Focus on modelling exoplanet transmission spectra, comparing to observations, and leading scientific publications.

Location: Hybrid (Milton Keynes, UK office) - some office attendance required when necessary.

Salary: £38,784 to £46,049

Company

The UK’s largest university, a world leader in flexible part-time education combining access to higher education with research excellence.

What you will do

• Develop, train, and test a neural network Mie scattering emulator using existing routines for training data.
• Integrate the emulator into the NemesisPy atmospheric model and apply to JWST data for hot Jupiter cloud analysis.
• Model exoplanet transmission spectra, compare to observations, and write telescope proposals for further data.
• Lead scientific publications, disseminate research at conferences, and support PhD students.
• Develop independence through leading observing proposals and coordinating international teams.

Requirements

• PhD in Astronomy, Astrophysics or related field.
• Experience in exoplanet atmosphere modelling OR applying machine learning (especially neural networks) to astrophysical data.
• Developing track record of peer-reviewed publications.
• Python programming for scientific data processing and analysis.
• Time management, project planning, effective presentation orally and in writing.
• Ability to work independently and in diverse teams.

Nice to have

• Experience in spectral retrieval of exoplanet atmospheres.
• Experience with JWST observations of exoplanets.

Culture & Benefits

• Flexible working discussions including job share, part-time, compressed hours.
• Hybrid work from home and Milton Keynes office.
• Range of benefits for work-life balance, staff development events.
• Health and safety compliance, equality policies.

Hiring process

• Submit CV and Supporting Statement (max 1000 words) addressing essential/desirable criteria.
• Shortlisted candidates interviewed on 20th or 21st May.