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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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pathways, specifically chromatin and small non-coding RNAs, in regulating gene expression in the parasitic nematode Strongyloides. In this role you will use Strongyloides epigenetic profiling data
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including Dr Keith Winwood (Manchester Met), and Prof Lukasz Kaczmarczyk (University of Glasgow, and founder of open-source finite element code MoFEM). Key Responsibilities The key technical responsibility
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. The salary for this post is at Grade UE07: £40,497 to £48,149 per annum, pro-rata if part-time. Your skills and attributes for success: PhD (or near completion) in a relevant field. Strong coding skills in
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good understanding of biomedical signal processing Proficiency in Python coding Knowledge of statistics and physiological signal analysis Good understanding of photoplethysmography and Near-infrared
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, enhancing, and running code in R. You will have excellent communication skills with the ability to talk to different audiences, as you will be collaborating with a team of researchers across multiple
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computer codes to solve some of the daily research problems and have experience with high performance computing. You should have a PhD in Chemistry, Physics or Materials Science with a proven research track
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neurogenetics of Drosophila. This requires expertise in setting up and analysing behavioural tests, using appropriate analytical methods and software and skills in coding in e.g. R, MatLab, R, Python, as required
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, enhancing, and running code in R. You will have excellent communication skills with the ability to talk to different audiences, as you will be collaborating with a team of researchers across multiple
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have experience in code development and/or use of first principles methods (e.g. DFT) and/or machine learning methods, as well as experience in working with experiments and/or experimental collaborators