Research Associate (Biostatistician), Cardiff University
The Institute of Infection &
Immunity at the Cardiff University School of Medicine seeks to appoint a
Research Associate / Biostatistician. The successful applicant will work in the
research group led by Dr Matthias Eberl on the identification and validation of
pathogen-specific biomarker signatures in patients with acute infections. The
position is funded for 18 months by Kidney Research UK and the National
Institute for Health Research (NIHR) within the Invention for Innovation (i4i)
programme.
Research in
the group of Dr Eberl is based upon the premise that each type of infection
evokes a distinct pathogen-specific host response (‘immune fingerprint’), and
aims to exploit the unique sophistication of the human immune system for
diagnostic purposes. A patient’s early anti-microbial response is likely to
provide far more detailed insight into the true cause and severity of
infections than conventional methods, independently of the subsequent clinical
course of the disease. Recent data in well-defined patient cohorts presenting
with symptoms of acute infections indicate that the immune responses evoked by
distinct types of organisms are characteristic enough to reveal fundamental
pathogen-specific differences. These cutting-edge findings directly inform the
development of point-of-care tests in primary and secondary care to target treatment
and improve patient management.
This vacancy
is for a Research Associate who will provide statistical support for ongoing
studies, contribute to the identification and validation of biomarker
signatures, and develop novel algorithms to mine large datasets, using binary
and multivariate logistic regression, decision trees, neural networks, ROC
curves and other advanced approaches.
The
post-holder will work across disciplinary boundaries, in close collaboration
with microbiologists, immunologist, clinicians and commercial partners,
embedded in all-Wales, UK-wide and international academic and clinical
networks.
The
post-holder will have a Degree in Statistics or in a relevant Biomedical
Sciences subject with a significant statistics component.
This post is
full time (35 hours per week) and is fixed term for 18 months.
The post is
available from 02/02/2015.
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