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Position: Postdoctoral Research Fellow - Computational Biology and Bioinformatics
Institution: University of Oxford
Location: Oxford, Oxfordshire, United Kingdom
Duties: We are seeking a highly motivated and talented Computational Biologist with experience in Next Generation Sequencing data analysis and machine-learning and/or statistical modelling to join our group to study the underlying rules of T cell receptor interaction with MHC presented peptides by leveraging multimodal single cell data from various cutting-edge technologies. Familiarity with TCR/BCR or antigen data is desirable but not essential for this post. The research in our group is focused on the use of systems/quantitative immunology to foster a better understanding of the mechanisms underpinning the regulation of adaptive immune system in healthy individuals. The aim of these studies is to pave the way to further our knowledge of functional and molecular mechanisms linked to dysregulation of the immune system in serious human health challenges such as cancers, infectious/autoimmune diseases and aging
Requirements: You will hold a PhD/Dphil of relevance to systems and quantitative immunology experience of research within bioinformatics. A strong background in machine-learning/or and statistical inference and/or data science is essential. You will possess the ability to independently plan and manage a research project. A background or knowledge in T and B cell Immunology and experience of computational biology of immune repertoire data (TCRs and BCRs) is desirable
   
Text: UK date and time: 22-September-2021 14:56 Applicant Options New Search Login Job Details Help Terms of Use & Privacy Policy Job Details Postdoctoral Research Fellow- Computational Biology and Bioinformatics RDM-Investigative Medicine, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU Grade 8: £42,149 - £50,296 per annum We are seeking a highly motivated and talented Computational Biologist with experience in Next Generation Sequencing data analysis and machine-learning and/or statistical modelling to join our group to study the underlying rules of T cell receptor interaction with MHC presented peptides by leveraging multimodal single cell data from various cutting-edge technologies. Familiarity with TCR/BCR or antigen data is desirable but not essential for this post. The research in our group is focused on the use of systems/quantitative immunology to foster a better understanding of the mechanisms underpinning the regulation of adaptive immune system in healthy individuals. The aim of these studies is to pave the way to further our knowledge of functional and molecular mechanisms linked to dysregulation of the immune system in serious human health challenges such as cancers, infectious/autoimmune diseases and aging. Over the past couple of decades owing to the cutting-edge advances in high throughput sequencing and single cell profiling technologies, the field of life science -especially immunology- has faced the challenge of unprecedented amount of very complex, multi-dimensional data. Understanding such data and extracting the sound biological knowledge has become more complicated than performing the experiments. As such, quantitative approaches including statistical inference and machine-learning techniques especially the cutting-edge deep neural networks have proven very successful. In this regard, the current research theme in our group is specifically focused on T cells response and function in which multi-modal high throughput sequencing ‘big data’ from the cutting-edge bulk and single cell technologies are incorporated into computational, machine-learning and statistical models to study T cell recognition of self and foreign pathogens. This post is to focus on developing machine-learning and statistical models to further advance our understanding of the rules underpinning T cell receptor recognition of its cognate peptides using single TCR and transcriptomics data. The work will involve collaboration with computational biologists in the group as well as with other immunologists in HIU undertaking antigen-specific (Prof. Simmons’ lab) and/or lipid-specific (Prof. Ogg’s lab) T cell experiments employing cutting edge single cell technologies. You will hold a PhD/Dphil of relevance to systems and quantitative immunology experience of research within bioinformatics. A strong background in machine-learning/or and statistical inference and/or data science is essential. You will possess the ability to independently plan and manage a research project. A background or knowledge in T and B cell Immunology and experience of computational biology of immune repertoire data (TCRs and BCRs) is desirable. The post is full-time and fixed-term for up to 2 years, with a possibility of extension. Flexible working can be discussed during the interview process. Applications for this vacancy are to be made online. You will be required to upload a supporting statement and CV as part of your online application. Only applications received before 12:00 midday on Friday 15 October 2021 will be considered. Contact Person : HR OFFICER Vacancy ID : 153395 Contact Phone : Closing Date & Time : 15-Oct-2021 12:00 Contact Email : hr@rdm.ox.ac.uk Click on the link(s) below to view documents Filesize Job Description 503 Return to Search Results Apply Now
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