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Position: Research Fellow
Institution: University College London
Department: UCL Queen Square Institute of Neurology
Location: London, United Kingdom
Duties: The project aims to create a prototype software that predicts whether an individual patient with MS will respond to a medication by using machine learning techniques (a crucial step towards "personalized medicine"). All adult patients with MS who are going to start a disease-modifying treatment within the next two years at UCLH NHS FT will be invited to join this study, which will also be extended to children initiating therapy at Great Ormond Street Hospital and associated UK centres. All the elements constituting an individual MS profile will be collected prospectively in a large-scale registry
Requirements: Applicants must have an Honours degree (minimum 2: 1) and a Higher Degree in a discipline related to this project or equivalent professional/industrial experience. Experience with clinical research in children with MS, laboratory (immunological or genetic) analysis, and analysis of MS scans is essential. An understanding of machine learning/high-dimensional models, practical experience with statistical analysis techniques, and experience of large-scale databases and multi-centre projects are also required, as are excellent oral and written communication skills and good inter-personal skills. Experience of PPE and PPI activities is desirable
   
Text: Research Fellow, - Ref:1792218 Click here to go back to search results Apply Now UCL Department / Division UCL Queen Square Institute of Neurology Specific unit / Sub department Department of Neuroinflammation Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) ?35,328 - ?40,437 per annum Duties and Responsibilities The NMR Research Unit is a multidisciplinary research team focusing on multiple sclerosis (MS). A Research Fellow is sought to contribute to the development and optimisation of a high-dimensional model to predict individual treatment responses in MS, as part of an NIHR Research Professorship awarded to Professor Olga Ciccarelli. This is a collaborative project with Dr Parashkev Nachev's team, who are working on the creation of individually predictive models of clinical outcome from high-dimensional analysis of large-scale clinical datasets. The project aims to create a prototype software that predicts whether an individual patient with MS will respond to a medication by using machine learning techniques (a crucial step towards "personalized medicine"). All adult patients with MS who are going to start a disease-modifying treatment within the next two years at UCLH NHS FT will be invited to join this study, which will also be extended to children initiating therapy at Great Ormond Street Hospital and associated UK centres. All the elements constituting an individual MS profile will be collected prospectively in a large-scale registry. The post holder will be primarily responsible for taking care of all aspects of the study relating to children with MS, including blood testing for genetic markers and immunological research, collection of clinical information and MRI scans, organising the project database on XNAT (www.xnat.org), and supporting the development of probabilistic, high-dimensional models that can achieve high individual predictive value. S/he will also contribute to public and patient engagement (PPE) and involvement (PPI) activities. Appropriate honorary NHS contracts will be sought from the relevant NHS Trusts, for which a DBS check will be required. The post is available immediately and is funded by a grant from the UK MS Society for the period to December 2021 in the first instance. Key Requirements Applicants must have an Honours degree (minimum 2:1) and a Higher Degree in a discipline related to this project or equivalent professional/industrial experience. Experience with clinical research in children with MS, laboratory (immunological or genetic) analysis, and analysis of MS scans is essential. An understanding of machine learning/high-dimensional models, practical experience with statistical analysis techniques, and experience of large-scale databases and multi-centre projects are also required, as are excellent oral and written communication skills and good inter-personal skills. Experience of PPE and PPI activities is desirable. Further Details A Job Description and Person Specification can be accessed at the bottom of this page. To apply for the vacancy, please click on the 'Apply Now' button below. If you have any queries regarding the vacancy or the application process, please contact Miss E Bertram, HR Manager, UCL Queen Square Institute of Neurology (email: IoN.HRAdmin@ucl.ac.uk). Informal enquiries welcome to Prof Olga Ciccarelli (email: o.ciccarelli@ucl.ac.uk) or Dr Parashkev Nachev (email: p.nachev@ucl.ac.uk). UCL Taking Action for Equality We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 25 Feb 2019 Latest time for the submission of applications 23:59 Interview date TBC Our department holds an Athena SWAN Silver award, in recognition of our commitment and demonstrable impact in advancing gender equality. Any offer of employment will be subject to a Disclosure and Barring Service (DBS) check. This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. Job Description and Person Specification Apply Now
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