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Position: Research Assistant/Research Fellow Bioinformatician: Computational Scientist with interest in Immunity
Institution: University College London
Department: Division of Infection and Immunity
Location: London, United Kingdom
Duties: Two positions for Research Assistant/Postdoctoral Research Fellow are available in the Innate2Adaptive group to carry out analysis and integration of high dimensional data (including global transcriptomics and high-throughput T cell receptor sequencing) from SARS-CoV-2 human challenge experiments. The aim is to identify immunological correlates of outcomes of infection and to develop multi-variable mechanistic models for the determinants of immune protection. The post holders will be based at the Cruciform Building on the main UCL Bloomsbury Campus. The roles will involve running established data processing pipelines, but will also require the drive and initiative to develop novel data analysis approaches as necessary
Requirements: Applicants should have a BSc Degree or equivalent and a PhD in a relevant subject if applying for the Grade 7, Research Fellow post. We will consider applicants from computational or biological backgrounds but proficiency in management and analysis of transcriptomic data, Python and Bash scripting, and familiarity with statistics/machine learning are essential requirements
   
Text: Research Assistant/Research Fellow Bioinformatician: Computational Scientist with interest in Immunity, - Ref:1880225 Click here to go back to search results Apply Now UCL Department / Division Division of Infection and Immunity Location of position London Grades 6-7 Hours Full Time Salary (inclusive of London allowance) Grade 6B £32,217 - £33,958 per annum or Grade 7 £36,770 - £44,388 per annum Duties and Responsibilities Two positions for Research Assistant/Postdoctoral Research Fellow are available in the Innate2Adaptive group to carry out analysis and integration of high dimensional data (including global transcriptomics and high-throughput T cell receptor sequencing) from SARS-CoV-2 human challenge experiments. The aim is to identify immunological correlates of outcomes of infection and to develop multi-variable mechanistic models for the determinants of immune protection. The post holders will be based at the Cruciform Building on the main UCL Bloomsbury Campus. The roles will involve running established data processing pipelines, but will also require the drive and initiative to develop novel data analysis approaches as necessary. The posts holders will work closely with "wet" lab scientists, clinician and computational biologists and will report to Professors Benny Chain and Mahdad Noursadeghi. The posts are for 1 year in the first instance and are available immediately. Key Requirements Applicants should have a BSc Degree or equivalent and a PhD in a relevant subject if applying for the Grade 7, Research Fellow post. We will consider applicants from computational or biological backgrounds but proficiency in management and analysis of transcriptomic data, Python and Bash scripting, and familiarity with statistics/ machine learning are essential requirements. Further Details A job description and person specification can be assessed at the bottom of this page. To apply for the vacancy please click on the "Apply Now" button below. Informal enquiries regarding the vacancies can be made by email to Professor Benny Chain at b.chain@ucl.ac.uk and Professor Mahdad Noursadeghi at m.noursadeghi@ucl.ac.uk. For enquiries relating to the application process, please contact Isabel Lubeiro at i.lubeiro@ucl.ac.uk. We particularly welcome female applicants and those from an ethnic minority, as they are under-represented within UCL at this level. UCL Taking Action for Equality Closing Date 1 Dec 2021 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. 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 & Person Specification PO for jobs.ac.uk Apply Now
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