Applications are invited for an experienced researcher to develop and validate advanced statistical methods for the analysis of data from a novel multiplexed sensor in the lungs and blood vessels. The post is part of a large Interdisciplinary Research Collaboration which involves: the development of novel chemical sensors and detectors; the development of inference methods to analyse the data produced and infer the concentration of various pathological processes present so as to provide doctors with information on the state of intensive care unit patients; and the testing of the methods in in-vitro, ex-vivo and in-vivo assay systems. The post will be supervised by Professor Chris Williams, School of Informatics, University of Edinburgh.
The successful candidate will be a probabilistic machine-learning researcher (or similar) keen to work on a challenging application area. The data will come from two sources: (i) spectral data (from surface-enhanced Raman spectroscopy, SERS), and (ii) imaging data from the lungs. These data will be used to infer the concentration of various pathogens present. The integration of information collected from different sources will be tackled using hierarchical Bayesian models. Over the duration of the project the richness and complexity the sensed data and the number of spectral signals will increase.
You will be self-motivated with the ability to take day-to-day responsibility for the progress of the proposed work and collaborate effectively with project partners from medicine, physics, chemistry and engineering. There is potential for innovative methodological developments in the modelling framework. The post offers the opportunity to work in a world-class machine-learning research environment, applying and extending cutting edge methods in an important application area.
The Engineering and Physical Sciences Research Council (EPSRC) have sponsored this GBP 11.5M Interdisciplinary Research Collaboration between the Universities of Edinburgh, Heriot Watt and Bath. The IRC brings together a set of internationally-recognised researchers led by a multidisciplinary team of academics who have world-class track records from fibre optic research through sensing and imaging, signal processing and machine learning through to clinical care. The IRC will focus on the creation of new healthcare technologies to address national and global health care challenges. Such technologies will enable earlier and better diagnosis by building on a combination of advanced engineering and strong fundamental science. The IRC is set to become a power house of fibre-based sensing and imaging expertise, stimulating innovation in research and delivering major benefits for patient care.
This is a readvertisement and previous applicants need not apply.
Vacancy Ref: : 028993
Closing date: 5 p.m. UK time on 12th May 2014
Duration: 2 years with possible extension
Informal enquiries about the position may be directed to Prof Chris Williams ckiw@inf.ed.ac.uk .
To apply, and for a full job specification, visit this link (vacancy 028993).
Chris Williams