[R-jobs] Machine-learning Scientist | George Institute for Global Health & The University of Oxford

Reza Khorshidi r@khor@h|d| @end|ng |rom gm@||@com
Sun Dec 22 00:24:38 CET 2013

Dear all,

The George Institute for Global Health at the University of Oxford is
seeking to appoint a machine-learning scientist to join its Healthcare
Innovation and Evaluation Programme. The successful candidate will support
the team in analysis/mining and visualisation of large healthcare and
biomedical informatics databases (i.e., 'Big Data� in healthcare), in order
to deliver actionable signals for healthcare decision making.

The initial work will focus on mining (e.g., testing hypotheses) several
large and complex datasets, including several hundred thousands of
individuals' health records from national hospital registries, primary care
records, UK Biobank, as well as data from several clinical trials. This is
to be followed by developing advanced predictive models (e.g., hierarchical
Bayesian models for classification / regression / segmentation, Gaussian
processes for health time-series analysis, ...), which will highlight
health risks and support the relevant decision-making processes.

The post-holder will have a PhD degree in machine learning,
(bio)statistics, biomedical engineering, or any other
{data+computation}-heavy field with an interest in analysing large and
complex datasets. The ideal candidate will also have a strong background in
R and/or Python; experience of C/C++, Java, D3/JS, and high-performance
computing will be a plus.

For informal inquires, please contact Francesca Moore:
francesca.moore using georgeinstitute.ox.ac.uk

Or follow the links below:



Best regards,
Reza Khorshidi, DPhil (Oxon)

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