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expected that the successful candidate will contribute to the computational analysis of multi-omic data that will be generated during the project. The candidate must hold or be near completion to a PhD/DPhil
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research materials and analysing and presenting qualitative and/or quantitative data from a variety of sources. The successful candidate will hold a PhD degree in a relevant topic (e.g. Biomedical sciences
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opportunities for these diseases. The project will use a wide variety of data processing, data analysis, and statistical techniques to functional genomic data (ChIP-seq, RNA-seq, ATAC-seq, co-accessibility
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well as proficiency in MATLAB, Python, or similar for real-time data analysis. Knowledge of implantable neural interfaces, electrophysiology, and stimulation technologies is also essential. Informal enquiries may be
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), based at the Centre for Human Genetics, University of Oxford. The post aims to assist with the preparation and molecular characterisation of tumours using multi-omic analysis focusing principally
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involve developing methods for complex trait analysis, scalable Bayesian and deep learning approaches, or algorithms for inferring and analysing large-scale graph data structures. Experience in statistical
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changes. In this role, you will take a lead on developing data analysis approaches and contribute to the overall study design and implementation. In particular, this will involve applying existing or even
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and computational biologists within the Buckley Group. The project will use CRISPR-based techniques and small molecules to manipulate expression of a cohort of transcription factors followed by analysis
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and/or R for data analysis and visualisation and have excellent communication skills. This is post is full-time, fixed term post for 2 years. The closing date for applications is noon on 9 May 2025. You
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animal behaviour, neural recordings in behaving animals and neurosurgical techniques. They will have experience with analysis of behavioural and neural data, strong quantitative skills and proficiency in