Postdoctoral Researcher in Machine Learning for Exoplanet Atmospheric Modelling (Milton Keynes, ENG, GB, MK7 6 AA)Salary: £46049.00 Change your career, change lives 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 You Tube by clicking this link). About the Role 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 Nemesis Py atmospheric model, and applying this to observational data from the James Webb Space Telescope to constrain hot Jupiter cloud composition. Key Responsibilities The person appointed to this post will undertake duties to include: Developing, training and testing a neural network Mie scattering emulator. Using existing Mie scattering routines to construct training and test data sets. Modelling exoplanet transmission spectra and comparing to observational data; duties may also include writing telescope proposals to obtain further data. Leading scientific publications related to the research outcomes. Working with, and providing day to day support to, Ph D students in exoplanet atmospheres. Disseminating the research at major national and international conferences. 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. About You Essential: Ph D 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. What's in it for you?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). Flexible working 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. Next steps in the Recruitment process If shortlisted, we anticipate interviews taking place on either 20th or 21st May. How to apply To apply for this role please submit the following document(s): CVSupporting 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.