You will develop novel probabilistic statistical machine learning methods to build causal predictive models available in the one-of-a-kind Novartis-Oxford MS (NO.MS) dataset as part of Oxford; Novartis Collaboration for AI in Medicine. The NO.MS is the largest and the most comprehensive dataset on multiple sclerosis (MS), a collection of data on over 40, 000 individuals measured longitudinally, some over a decade
Requirements:
It is essential that you hold a PhD/DPhil in Statistics, Statistical Machine Biostatistics, Statistical Genetics or similar subject with post-qualification research experience and the ability to develop research projects with a strong publication record in peer-reviewed journals and conferences. You will have good understanding and potential to implement statistical techniques used in clinical studies/genomic research, and experience in high-throughput data analysis, integration and interpretation (e.g. high-throughput sequencing, proteomics, array-based technologies, etc.), preferably in human diseases
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Senior Postdoctoral Researcher in Biostatistics: Statistical Machine Learning and Image Analysis Big Data Institute, Li Ka Shing Centre for Health Information and Discovery Old Road Campus, Headington, Oxford, OX3 7LF Additional location: Department of Statistics, 24-29 St Giles’, Oxford, OX1 3LB We are looking to appoint a Senior Researcher in Biostatistics: Statistical Machine Learning and Image Analysis to join the Oxford-Novartis Collaboration in AI Medicine team at the Big Data Institute, Nuffield Department of Medicine. You will develop novel probabilistic statistical machine learning methods to build causal predictive models available in the one-of-a-kind Novartis-Oxford MS (NO.MS) dataset as part of Oxford-Novartis Collaboration for AI in Medicine. The NO.MS is the largest and the most comprehensive dataset on multiple sclerosis (MS), a collection of data on over 40,000 individuals measured longitudinally, some over a decade. Under the line management of Dr. Habib Ganjgahi and close collaboration with Professors Chris Holmes and Thomas Nichols, you will apply and develop state of the art causal scalable statistical machine learning prognostic models to identify factors and early change-parameters in clinical and MRI images that, on an individual patient level, contribute to a reliable prediction of time to long-term outcomes using clinical, laboratory and high-dimensional image data that can handle missing data and different data modalities and building individual treatment response models to predict which subjects will respond to treatment and heterogenous treatment effect. It is essential that you hold a PhD/DPhil in Statistics, Statistical Machine Biostatistics, Statistical Genetics or similar subject with post-qualification research experience and the ability to develop research projects with a strong publication record in peer-reviewed journals and conferences. You will have good understanding and potential to implement statistical techniques used in clinical studies/genomic research, and experience in high-throughput data analysis, integration and interpretation (e.g. high-throughput sequencing, proteomics, array-based technologies, etc.), preferably in human diseases. Applications for this vacancy are to be made online and you will be required to upload a supporting statement and CV as part of your online application. Your supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. This position is offered full time on a fixed term contract until 31 August 2027 and is funded by Novartis. Only applications received before 12 midday on Monday 14 October 2024 will be considered. Please quote 173015 on all correspondence. Contact Person : Margarita Monroy Vacancy ID : 173015 Contact Phone : 01865287757 Closing Date & Time : 14-Oct-2024 12:00 Pay Scale : STANDARD GRADE 8 Contact Email : recruitment@ndm.ox.ac.uk Salary (£) : Salary in range £47,085 - £52,783 per annum. This is inclusive of a pensionable Oxford University Weighting of £1,500 per year (pro rata). var links = document.querySelectorAll(".targetLink"), i, j, aTags, string; for(i=0; i < links.length; i ){ aTags = links[i].querySelectorAll("a for(j=0; j < aTags.length; j ){ string = aTags[j].href; if(string.indexOf("javascript") === -1) { aTags[j].target = "_blank"; } } } Click on the link(s) below to view documents Filesize 173015 - Senior Postdoctoral Researcher in Biostatistics - JD 276.7
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