14 parallel-computing-numerical-methods Fellowship research jobs at University of London
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a Research Fellow to contribute to a research programme examining how digital environments influence adolescent health. The postholder will lead the analysis of the UK Household Longitudinal Study
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& International Health is seeking to appoint a Research Fellow in Health Data Science (with a focus on machine learning) to NeoShield , a multi-country implementation research programme focused on neonatal sepsis
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and feature extraction. They will also assess and mitigate biases in social media data and design evidence-based heuristics to guide researchers in applying these methods effectively. The post-holder
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(PHES) is seeking to appoint a Research Fellow to contribute to the UKRI-funded Local Health and Global Profits programme, a national research consortium led by the University of Bath and involving
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doctoral degree, in a relevant topic and will ideally have skills in quantitative methods and some knowledge of public health research linked to diet/food. For one of the two posts we particularly encourage
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designing study protocols and submitting ethics applications; qualitative research using NVivo or similar analysis software; mixed-methods research; statistical analysis; training and supervising teams
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. This Bart’s Charity Funded project will focus on developing, implementing, and evaluating a psychosocial support programme for people affected by nitrous oxide related harms. The post-holder will be supported
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for the Treatment of Acute Limb Ischaemia The postholder must have a postgraduate degree, ideally a doctoral degree, in a relevant topic and should have formal training in economic evaluation and related methods
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software packages. They also must have demonstrated knowledge of longitudinal data analysis methods, and an understanding of sample size calculations. Further particulars are included in the job description
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endemic countries. We are seeking to appoint a Research Fellow to join a research programme that applies advanced bioinformatic, statistical, and population genomic approaches to large-scale sequencing data