[David Dowe sent me the following ad for a position of research fellow in statistics, machine learning, and Astrophysics at Monash University, Melbourne.]
RESEARCH FELLOW: in Statistics and Machine Learning for Astrophysics, Monash University, Australia, deadline 31 July.
We seek to fill a 2.5 year post-doctoral fellowship dedicated to extensions and applications of the Bayesian Minimum Message Length (MML) technique to the analysis of spectroscopic data from recent large astronomical surveys, such as GALAH (GALactic Archaeology with HERMES). The position is based jointly within the Monash Centre for Astrophysics (MoCA, in the School of Physics and Astronomy) and the Faculty of Information Technology (FIT).
The successful applicant will develop and extend the MML method as needed, applying it to spectroscopic data from the GALAH project, with an aim to understanding nucleosynthesis in stars as well as the formation and evolution of our Galaxy (“galactic archaeology”). The position is based at the Clayton campus (in suburban Melbourne, Australia) of Monash University, which hosts approximately 56,000 equivalent full-time students spread across its Australian and off-shore campuses, and approximately 3500 academic staff.The successful applicant will work with world experts in both the Bayesian information-theoretic MML method as well as nuclear astrophysics. The immediate supervisors will be Professor John Lattanzio (MoCA), Associate Professor David Dowe (FIT) and Dr Aldeida Aleti (FIT).