The Department of Physics & Astronomy at the University College London (UCL) invites applications for a Postdoctoral Research Associate Position in the field of Extrasolar Planets. The successful applicant will be part of the European Research Council funded ExoAI project and work closely with Dr Waldmann (PI of ExoAI) on developing machine and deep learning methods to characterise exoplanet atmospheres.
The PDRA position is for the duration of 2 years in the first instance with a salary starting from £34,635.
The successful candidate will have the opportunity to work on a wide range of statistical learning problems, ranging from observational data analysis (HST and JWST data) to modelling of planetary atmospheres. He/she will be joining a dynamic exoplanet group and one of the largest astrophysics and planetary science departments in the UK. The applicant will have access to state-of-the-art equipment (dedicated clusters, HPC facilities, cloud computing) and will benefit from a wealth of expertise already in-house.
While the post-holder will spend a significant amount of time at UCL, this work entails close collaborations with EU and US institutes and the applicant should be able to travel abroad frequently for collaborations and conferences.
Key Requirements
The applicant should have good knowledge of machine learning, statistical techniques and a track record in either data analysis or statistical modelling. Good programming skills in Python and/or C++/Fortran are essential. Furthermore, experience with Tensorflow/Theano/Keras or similar is desirable. Prior exposure to exoplanet research is advantageous but not required.
Among the duties and responsibilities, he/she will help with the supervision of MSc and PhD students hired as part of the ExoAI team at UCL and the management of the project resources. The postholder will independently submit papers to peer reviewed journals and will contribute to the drafting and submitting of papers of the group in a collaborative manner.
For further information and a link to the application form, please follow the URL to the UCL job posting.