ACAD107801

Applications are invited for a Research Associate/Senior Research Associate position to study the atmosphere of Titan using mid-infrared spectroscopic data. The successful applicant will study seasonal changes in Titan's complex atmosphere using data from the Cassini spacecraft's Composite InfraRed Spectrometer (CIRS), which is sensitive to stratospheric composition and temperature. The project may also involve data from Cassini's other remote sensing instruments, ground-based and space-based telescopes, and numerical models to allow more complete interpretations. The PDRA will be part of the geophysics group in the University of Bristol's School of Earth Sciences and be working under the planetary formation, structure, and dynamics theme. The post is initially for 2 years with a possible extension to 3 years, subject to funding.

What will you be doing?

The post-holder will analyse infrared spectra of Titan using radiative transfer or other appropriate remote sensing methods to investigate seasonal atmospheric changes and photochemical processes. They will also develop new methods of analysis as necessary, compare results to atmospheric models for interpretation (e.g. dynamical general circulation models and photochemical models), and develop simplified atmospheric models to assist interpretation as required. They will publish results in peer-reviewed journals, disseminate results through academic conferences and other appropriate outlets, and contribute to existing collaborations or develop new ones as required.

The successful candidate will hold (or will shortly obtain) a PhD in a relevant physical sciences subject and be highly independent and self-motivated. They will have demonstrated research ability in radiative transfer of Titan's atmosphere using the NEMESIS analysis software. They will have experience with processing space-based or ground-based infrared measurements evidenced by publications, including observations from Cassini's Composite InfraRed Spectrometer. They will have experience with processing and analysis of large planetary datasets, including the numerical methods required for analysis and interpretation of data and model output. They will also have significant experience in scientific programming including FORTRAN, Matlab, Python, IDL, shell scripting, and Unix.