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Position: PhD Studentship On Computational Clinical Electrophysiology
Institution: University College London
Department: Institute of Cardiovascular Science
Location: London, United Kingdom
Duties: Life-threatening ventricular tachycardia (LTVT) has a dramatic impact on the life of hundreds of thousands of people and their families worldwide. In the last decade, catheter ablation has become a standard procedure for treating LTVT, but its current success rate remains unacceptably low there and there is an urgent need to transform this procedure into an effective, safe, and rapid treatment for LTVT. This procedure relies upon intracardiac mapping of the electrophysiological substrate, identification of cardiac sites supporting the LTVT and their catheter ablation. One of the most compelling factors limiting the effectiveness of this procedure is the lack of research in data-science applied to intracardiac mapping. In recent years, electro-anatomical mapping systems have revolutionised cardiac mapping and can now collect a vast amount of data, but most techniques to identify ablation targets are still based on simplistic metrics and/or qualitative assessment
Requirements: This is a highly interdisciplinary project, and applications are encouraged from a range of backgrounds. The student should hold an undergraduate or Master degree in biomedical engineering, computer science, physics, health informatics (or a related subject), awarded at 2: 1 level (UK system or equivalent) or above
   
Text: PhD Studentship On Computational Clinical Electrophysiology, - Ref:1885628 Click here to go back to search results Apply Now UCL Department / Division Institute of Cardiovascular Science Location of position London Duration of Studentship 3 years Stipend £18,000 Vacancy Information Life-threatening ventricular tachycardia (LTVT) has a dramatic impact on the life of hundreds of thousands of people and their families worldwide. In the last decade, catheter ablation has become a standard procedure for treating LTVT, but its current success rate remains unacceptably low there and there is an urgent need to transform this procedure into an effective, safe, and rapid treatment for LTVT. This procedure relies upon intracardiac mapping of the electrophysiological substrate, identification of cardiac sites supporting the LTVT and their catheter ablation. One of the most compelling factors limiting the effectiveness of this procedure is the lack of research in data-science applied to intracardiac mapping. In recent years, electro-anatomical mapping systems have revolutionised cardiac mapping and can now collect a vast amount of data, but most techniques to identify ablation targets are still based on simplistic metrics and/or qualitative assessment. The overarching aim of the project is to improve the outcome of LTVT catheter ablation, a truly life-saving procedure. The student will propose computational, data-driven, solution to improve the efficacy and safety of the procedure while reducing its risk and cost. Specific aims include: · Establish accuracy and limitation of state-of-the-art electro-anatomical mapping systems through reproducibility assessment of cardiac mapping. · Assessment of novel strategies for revealing the arrhythmogenic substrate. · Using advanced signal processing and machine learning for automatic identification of ablation targets. Studentship Description The student will join a multidisciplinary team composed of world leading cardiologists and data scientists and will work on unique data sets collected during clinical procedures using state of the art medical technology for cardiac mapping. The student will benefit from extensive research and training resources at UCL. The UCL Institute of Cardiovascular Science is a world-class centre of excellence focussed on developing novel preventative and therapeutic strategies in cardiovascular medicine. The institute brings together basic and clinical scientists from UCL and expert clinicians from UCL partner hospitals. Further information can be found online https://www.ucl.ac.uk/cardiovascular/ucl-institute-cardiovascular-science The project is a collaboration between data-scientist at UCL and clinicians at the Barts Heart Centre, the largest cardiovascular clinical centre in Europe. Person Specification This is a highly interdisciplinary project, and applications are encouraged from a range of backgrounds. The student should hold an undergraduate or Master degree in biomedical engineering, computer science, physics, health informatics (or a related subject), awarded at 2:1 level (UK system or equivalent) or above. Excellent organisational, interpersonal, and communication skills, along with a stated interest in interdisciplinary research, are essential. Previous experience in computing is required and skills is signal processing and machine learning are highly desirable. The studentship is available for three years starting from September/October 2022 and includes tax free stipend, tuition fees (full-time, home students fees) and research costs. Eligibility Application Applicants should first contact Dr Michele Orini (m.orini@ucl.ac.uk) quoting the job reference. Please enclose a statement outlining suitability for the project (1 page maximum) and two pages CV (including contact details of two referees). The supervisory team will arrange interviews for short-listed candidates. After interview, the successful candidate will be given instructions to formally apply online via the UCL website. Contact name Dr Michele Orini Contact details m.orini@ucl.ac.uk Contact name Michele Orini Contact details m.orini@ucl.ac.uk UCL Taking Action for Equality Closing Date 10 Jul 2022 Latest time for the submission of applications midnight Interview date TBC Studentship Start Date 26 September 2022 Apply Now
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