The role will specifically involve the analysis of transcriptomic data from multiple independent cohorts of patients with AML that have been generated by our laboratory scientists. However, independent, self-motivated dry-lab approaches (i.e., the analysis of public transcriptomic/proteomic AML datasets) will also be encouraged
PhD in a relevant subject and a strong and proven research experience or interest in systems immunology and computational biology
Research Fellow in Computational Biology Job Reference : 05717 Location : Clifton Campus Closing Date : 02/12/2018 Salary : Grade G (£27,830 - £32,236 p.a.) Department : College of Science and Technology School/Section : School of Science & Technology Post Ref : S4668 Get Directions Successful. Confident. Ambitious. Innovative - just a few words that are used to describe us. Topped with our focus on award-winning research, professional expertise and strategic partnerships, we really do offer a great working environment for everyone. 2017 has been a year full of prizes, publicity and recognition for the NTU community, culminating in our receipt of the prestigious University of the Year award . Along the way, we’ve recorded some of the highest student satisfaction levels in the country in the 2017 National Student Survey, and achieved the TEF gold standard for the quality of our teaching. We are also extremely proud to have been named Modern University of the Year in the Times and Sunday Times Good University Guide 2018 . All of these achievements are testament to the passion, ideas and ambition of our workforce. We recognise that our rise up the league tables is thanks to harnessing the creativity and talent of our people. Join us, at this exciting time and take your career to the next level too. The Leukaemia Immunotherapy group is using transcriptomic approaches to discover immune gene signatures that predict clinical response of patients with acute myeloid leukaemia (AML) to immunotherapy. Genomics data are further complemented by a broad range of experimental in vitro leukaemia models. This line of research will ultimately provide a compendium for sophisticated integrative data analysis, modelling and visualisation, with the ultimate goal to deliver personalised immunotherapy to patients with AML. The role will specifically involve the analysis of transcriptomic data from multiple independent cohorts of patients with AML that have been generated by our laboratory scientists. However, independent, self-motivated dry-lab approaches (i.e., the analysis of public transcriptomic/proteomic AML datasets) will also be encouraged. We are an interdisciplinary team with expertise in leukaemia biology and treatment, cancer genomics and bioinformatics. Applications are welcome from candidates with a PhD in a relevant subject and a strong and proven research experience or interest in systems immunology and computational biology. Additional Information: This post is being offered on a fixed-term contract for 12 months (5 days/week). Interview date: Week Commencing 10th of December, 2018 If you have any specific queries in relation to this position, please contact Professor Sergio Rutella, Professor of Cancer Immunotherapy via email at email@example.com. To submit an online application for this position please visit www.ntu.ac.uk/vacancies. If you require documentation in alternative formats (e.g. Braille, large print) please contact us at firstname.lastname@example.org S4668 - Research Fellow in Computational Biology - Job description S4668 - Research Fellow in Computational Biology - Person Specification
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