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analysis. Define genetically defined and non-defined PD, MSA, HSP, RED phenotypes. Re-analyse short read exome and genome data. Long-read DNA sequencing and analysis in select genetically negative families
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in screening informatics, biological data analysis, and drug discovery workflows to support the development and delivery of screening and pharmacology programmes within the ARUK UCL Drug Discovery
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be with UCL colleagues, you will be expected to develop positive working relationships with ICGNMD researchers across the UK and internationally, therefore strong communication and data reporting
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, including maintenance, optimisation, and scale is essential. Experience with single-cell data analysis will also be essential. Experience with liquid handling robotics would also be beneficial. The candidate
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systems, their implementations and data analysis methodologies. Practical experience of deploying IP cores on FPGA systems is essential. A track record of publications in leading journals / conferences is
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with morphological image data is essential. Experience in geometric morphometrics and/or finite element analysis is desirable. Customer advert reference: B02-10342
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data is essential. Experience in geometric morphometrics and/or finite element analysis is desirable. The UCL Ways of Working supports colleagues to be successful and happy at UCL through sharing
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understanding of human genetics. Knowledge of DNA and RNA sequencing analysis, of programming languages such as R, Python, or Bash script, and of bioinformatics pipelines for genomic data analysis is essential
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instance. About you The successful candidate will have skills in advanced quantitative methods including longitudinal data analysis using large-scale administrative and cohort data. Further particulars
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analyse large scale job application data from employers using quantitative methods. Findings from the analysis will be written up in a project report, separate reports to employers, and in academic journal