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Position: Postdoctoral Researcher - Neuroimaging Harmonisation Methodology
Institution: University of Oxford
Location: Oxford, Oxfordshire, United Kingdom
Duties: The main focus of the role will be developing methods for harmonising neuroimaging datasets. You will conduct research involving measuring bias using several specifically acquired harmonisation datasets, as well as developing tailored image pre-processing and/or post-processing methods to minimise bias and reduce variation. The research will also include the development of general analytic methods for matching, normalising and integrating data across studies, using statistical and machine learning approaches
Requirements: The research requires experience in MRI-based neuroimaging acquisition and/or analysis along with expertise in programming (matlab, python, C++ and/or shell scripting are preferred). You should hold a Master's degree or PhD in a relevant quantitative subject (such as engineering, physics, mathematics or statistics) and have experience of processing and analysing large datasets
   
Text: Postdoctoral Researcher in Neuroimaging Harmonisation Methodology Nuffield Department of Clinical Neurosciences (NDCN), FMRIB, University of Oxford, John Radcliffe Hospital, Oxford Grade 7: £31,076 - £38,183 p.a. An exciting opportunity has arisen to become a postdoctoral researcher and member of the analysis research group that forms part of the FMRIB Centre, which is a part of the Wellcome Centre for Integrative Neuroimaging and the University of Oxford. The main focus of the role will be developing methods for harmonising neuroimaging datasets. Harmonisation of data across studies is an important challenge in many areas of science. One particular aim is to be able to take a large dataset, such as the 100,000 subjects in the UK Biobank study, and use these as normative data for images collected separately (e.g., individual patients or research cohorts). Owing to variations in hardware and scanning protocols, consistent biases exist in the images and derived measurements and the objective of this research is to increase our understanding of these variations, how they affect various quantitative measures, and develop techniques for reducing these biases. You will conduct research involving measuring bias using several specifically acquired harmonisation datasets, as well as developing tailored image pre-processing and/or post-processing methods to minimise bias and reduce variation. The research will also include the development of general analytic methods for matching, normalising and integrating data across studies, using statistical and machine learning approaches. The research requires experience in MRI-based neuroimaging acquisition and/or analysis along with expertise in programming (matlab, python, C++ and/or shell scripting are preferred). You should hold a Master's degree or PhD in a relevant quantitative subject (such as engineering, physics, mathematics or statistics) and have experience of processing and analysing large datasets. It is advantageous to have experience with the FSL software and/or MR physics and MRI analysis techniques. You would ideally have previous experience in developing novel methodology and/or using machine learning techniques. For further details please contact Professor Mark Jenkinson: mark.jenkinson@ndcn.ox.ac.uk . The post is full-time for a fixed-term for 2 years in the first instance. Only applications received before 12.00 midday on Thursday 20 July 2017 will be considered. Interviews will be held as soon as possible thereafter. Contact Person : Claire Stevens Vacancy ID : 128675 Contact Phone : 01865 234781 Closing Date : 20-Jul-2017 Contact Email : hr@ndcn.ox.ac.uk Click on the link(s) below to view documents Filesize 128675_Postdoc Researcher_JD 1068.3
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