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 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").
A popular paper relating MML to Solomonoff-Kolmogorov complexity and algorithmic information theory (AIT) is Wallace and Dowe (1999a), ``Minimum Message Length and Kolmogorov Complexity'', Computer J, special issue on Kolmogorov complexity. Further reading on MML in the 2011 Elsevier Handbook of the Philosophy of Science (Vol. 7, Philosophy of Statistics) [including, e.g., dealing with a Neyman-Scott-like problem for panel data] is in Dowe (2011a), a nice accessible introduction is here, discussion of MML Bayesian nets with both continuous and discrete attributes is in Comley and Dowe (2003, 2005) [and with latent variable nodes here]; and further reading on MML (hybrid) mixture modelling is in Wallace and Dowe (2000) or sec. 6.8 of Wallace (2005) (with a spatial correlation model here).
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. Monash is committed to growing its already established excellence in astrophysics as well as machine learning and statistical inference. MML research at Monash University dates back to the original seminal Wallace and Boulton (1968), ``An information measure for classification'', Computer J. 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).
Monash University is based in Melbourne, named the world's most livable city in each of the last 5 years. Melbourne is a highly multi-cultural cosmopolitan city providing extensive cultural and lifestyle opportunities, is situated on the coast with excellent beaches readily accessible, many fine restaurants, etc.
Salary will be in the range AUD86,209 to AUD92,541, which includes a 9.5% contribution to superannuation from the University.
Cheers and best,
David Dowe.