AYUDAS A LA MOVILIDAD DE INVESTIGADORES/AS – NILS SCIENCE AND SUSTAINABILITY
9 January 2014PhD studentship Social Statistics University of Manchester
9 January 2014AYUDAS A LA MOVILIDAD DE INVESTIGADORES/AS – NILS SCIENCE AND SUSTAINABILITY
9 January 2014PhD studentship Social Statistics University of Manchester
9 January 2014We are seeking two full-time probabilistic programming postdocs to join Dr. Frank Wood’s research group at the Department of (Information) Engineering Science at Oxford. The posts are funded by DARPA under its Probabilistic Programming for Advanced Machine Learning program (http://tinyurl.com/fwoxpp) and are available immediately.
Oxford is part of a MIT/Oxford/Cambridge collaborative team. Dr. Wood (in Engineering) and Dr. Nando de Freitas (in Computer Science) are tasked with engaging in research on general-purpose inference and probabilistic programming applications. Oxford participants are already closely collaborating with both MIT (Dr. Vikash Mansingkha and Dr. Joshua Tenenbaum) on the development of a practical, scalable probabilistic programming environment and Cambridge (Dr. Zoubin Ghahramani) on models, inference, and applications. Candidates will be responsible for conducting wide-ranging, largely self-determined research at the intersection of probability, statistics, inference, modeling, compiler and language theory, and applications. Candidates will also be responsible for contributing to the development of a practical, deployable, scalable probabilistic programming system. Candidates will be expected to travel between sites and to collaborate widely.
Ideal candidates will possess
a) a strong machine learning background (with strengths in unsupervised generative modeling, general-purpose sampling-based inference, and Bayesian nonparametrics),
b) a strong computer science background (with strengths in automata theory, compiler and interpreter design, and practical functional coding ability) and
c) a strong inference and probability theory background. Candidates with excellent inference and languages theoretical backgrounds are particularly encouraged to apply.
Candidates must possess a PhD in computer science, statistics, or another closely related discipline.
Informal enquiries may be addressed to Frank Wood (email: fwood@robots.ox.ac.uk). Please include “[PPAML PDRA]” in the subject line.
More information can be found under id 111173 on http://www.eng.ox.ac.uk/about-us/jobs