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Faculty of Life Sciences and Medicine Hub for Applied Bioinformatics). We are looking for an ambitious candidate with established expertise in bioinformatics, specifically dealing with large data sets and
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practical workshops, and we recently partnered with KCL’s Spatial Biology Facility , an advanced centre equipped for high-resolution spatial transcriptomics and multiplex imaging, to turn large-scale data
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transcriptomics data analysis and interpretation Desirable criteria Contribution to open-source bioinformatics tools Hands-on experience with machine-learning frameworks Downloading a copy of our Job Description
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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Medicine Hub for Applied Bioinformatics). We are looking for an ambitious candidate with established expertise in bioinformatics, specifically dealing with large data sets and data integration. Knowledge
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for Research Staff Development for more information. About You To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in
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transcriptomics data analysis and interpretation Desirable criteria Contribution to open-source bioinformatics tools Hands-on experience with machine-learning frameworks Downloading a copy of our Job Description
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transcriptomics data analysis and interpretation Desirable criteria Contribution to open-source bioinformatics tools Hands-on experience with machine-learning frameworks Downloading a copy of our Job Description
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. You will also be responsible for implementing the model as a computer simulation and analysing it within a health-economics framework using standard computational techniques. You will also be
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working with NLP in general and LLMs in particular. They will also help to further develop machine learning models to predict clinical outcomes. Familiarity with current methods in this area is essential