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Certificate Examination (SCE) Proven competency in Python, R, and Stata coding Experience in systematic reviews and meta-analyses, including Bayesian methods Clinical experience in rheumatology, including
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systematic reviews and meta-analyses, including Bayesian methods Clinical experience in rheumatology, including outpatient clinics Desirable Criteria: Higher degree (MD/PhD) in a relevant field Record of peer
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following skills and experience: Essential criteria PhD in statistical/psychiatric/behavioural genetics or a related academic area with a strong data analysis component Excellent coding skills with a focus on
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Completed core medical training and currently in higher specialty training Interest in translational cancer research Understanding of clinical research methods and GCP Experience in academic/research
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Evaluation (CMHPE), utilising their mixed methods their mixed-methods (ideally qualitative and quantitative) expertise. The role includes planning, coordinating, executing, and reporting on evaluation and
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for this role. This role will involve developing and applying analysis plans using a variety of advanced methods with the support of project supervisors. The postholder will have completed a PhD in a relevant
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of genome organisation and metabolic control - with the bold vision of building synthetic life. In this role, you will develop and apply deep learning methods to analyse single-cell modalities, focusing
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-seq datasets, and applying advanced statistical and machine-learning methods (AI/ML) to extract novel biological insights that drive our translational and fundamental research programmes. In
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of breast/glioma/melanoma cancer animal models. Experience in contributing to publications with writing up materials and methods referring to histological aspects. MSc degree or equivalent in a relevant
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spatial transcriptomics and imaging genomics projects, integrating bulk and single-cell RNA-seq datasets, and applying advanced statistical and machine-learning methods (AI/ML) to extract novel biological