Postdoctoral Researcher in Machine Learning for Exoplanet Atmospheric Modelling

The Open University is the UK’s largest university, a world leader in flexible part-time education combining a mission to widen access to higher education with research excellence, transforming lives through education. Find out more about us and our mission by watching this short video (you will be taken to YouTube by clicking this link).

The School of Physical Sciences at the Open University, UK, invites applications for a 3-year fixed-term postdoctoral researcher in machine learning for exoplanet atmosphere modelling. The postdoctoral researcher will work with Dr Joanna Barstow and Dr Hugh Dickinson as part of the STFC-funded research project 'Rainbow Connection: Exoplanet Cloud Scattering Via Neural Networks'. The role will involve developing a neural network-based emulator for Mie scattering calculations, integrating the emulator into the NemesisPy atmospheric model, and applying this to observational data from the James Webb Space Telescope to constrain hot Jupiter cloud composition.

The person appointed to this post will undertake duties to include:

1. Developing, training and testing a neural network Mie scattering emulator.
2. Using existing Mie scattering routines to construct training and test data sets.
3. Modelling exoplanet transmission spectra and comparing to observational data; duties may also include writing telescope proposals to obtain further data.
4. Leading scientific publications related to the research outcomes.
5. Working with, and providing day to day support to, PhD students in exoplanet atmospheres.
6. Disseminating the research at major national and international conferences.
7. Developing their own independence by leading observing proposals, and leading and/or co-ordinating work within international teams.

All Staff are expected to:

• Co-operate with the Open University in ensuring as far as is necessary, that Statutory Requirements, Codes of Practice, University Policies and Departmental Health and Safety arrangements are complied with.
• Ability to carry out the role in a way that is consistent with equality legislation and University policies.
• Attend /complete appropriate staff development events / courses.

Essential:

• PhD in Astronomy, Astrophysics or a related field.
• Experience in modelling exoplanet atmospheres OR experience in applying machine learning techniques, especially neural networks, to astrophysical data.
• A developing track record of peer-reviewed publications in international journals.
• Experience of Python programming for scientific data processing and analysis.
• Time management and project planning skills.
• The ability to present your research effectively both orally and in scientific writing.
• The ability to work both independently and as part of a diverse team.

Desirable:

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

Support with your application

If you have any questions, or need support or adjustments relating to your application, the recruitment process, or the role, please contact us on 01908 541111 or email careers@open.ac.uk quoting the advert reference number.

At The Open University, we offer a range of benefits to recognise and reward great work, alongside policies and flexible working that contribute towards a great work life balance. Get all the details of what benefits we offer by visiting our Staff Benefits page (clicking this link will open a new window).

We are open to discussions about flexible working. Whether it’s a job share, part time, compressed hours or another working arrangement. Please reach out to us to discuss what works best for you.

Work location

It is anticipated that a hybrid working pattern can be adopted for this role, where the successful candidate can work from home and the office. However, as this role is contractually aligned to our Milton Keynes office it is expected that some attendance in the office will be required when necessary and in response to business needs.

If shortlisted, we anticipate interviews taking place on either 20th or 21st May. 

To apply for this role please submit the following document(s):

• CV
• Supporting Statement (Your Supporting Statement should be no more than 1000 words and should outline how your skills and experience meet the essential and desirable criteria listed above)

You can view your progress and application communications when you are logged into our recruitment system.  Please check your spam/junk folders if you do not receive associated email updates.

If you have any queries or questions about the recruitment process, or regarding your application, please contact: Careers@open.ac.uk.

The Open University is committed to equality, diversity and inclusion which is reflected in our mission to be open to people, places, methods and ideas. We aim to foster a diverse and inclusive environment so that all in our OU community can reach their potential.  We recognise that different people bring different perspectives, ideas, knowledge, and culture, and that this difference brings great strength.  We strive to recruit, retain and develop the careers of a diverse pool of students and staff, and particularly encourage applications from all underrepresented groups. We also aspire to make The Open University a supportive workplace for all through our policies, services and staff networks.