Sheffield University is advertising a PhD position in Computational Bioengineering whose challenge is to deploy personalised Virtual Physiological Human Models in clinical practice. The deadline for application is August 31st, 2012.
The overall aim of the project is to develop an optimised environment that could support large scale clinical trials involving individualised multi-scale models from the Virtual Physiological Human initiative. The PhD thesis will focus primarily on aspects of interoperability with the rest of the clinical ICT environment, of usability by an interdisciplinary team of clinical and bioengineering experts, and of scalability for the solution of computationally intensive models often featuring large stochastic simulations and/or highly coupled multi-scale models.
A re-factored implementation of the VPHOP Hypermodelling technology, based on the MAF3/CTK Bus Module, will be integrated with front-end data management services of the VPH-Share infrastructure, and with back-end clinical research data management services of the Sheffield Teaching Hospital Trust. Interactive software tools developed with the GIMIAS and MAF software frameworks will be integrated in the hypermodelling environment, together with both commercial and custom-made solvers and processing libraries. All these technologies will be deployed within the Sheffield Teaching Hospitals Trust, with workflows configured to support specific clinical trials. We foresee at least two applications, one in the prediction of the risk of fracture in osteoporotic patients, and one in coronary artery disease. Using these pilot workflows as reference the PhD thesis will concentrate on the adaptations required to optimise the efficiency, the usability, and the cost associated with the large scale use of these individualised simulations in clinical practice.
The ideal candidate should have first or upper second class honours or equivalent degree in Computer Science, Engineering, or Physics, with a strong orientation toward computational biomedical sciences. Familiarity with at least some of the relevant Information Technologies would be a major advantage. These might include databases, web services, C++ programming, Python programming, Java programming, scientific visualisation, interactive interfaces, numerical solution of physics-based models including finite element and computational fluid dynamics models, high performance computing, security and encryption, etc.
Interested candidates should in the first instance contact Prof DR Hose (d.r.hose@sheffield.ac.uk).
Please complete a University Postgraduate Research Application form and provide at least two references. To apply please visit http://www.shef.ac.uk/postgraduate/research/apply
http://www.shef.ac.uk/cardiovascularscience/groups/medphys
http://www.sheffield.ac.uk/mecheng/index
