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or related discipline to develop their data analysis and modelling skills and experience, applied to the field of health economics. We wish to encourage people who have strong quantitative skills who may be
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working full-time. An exciting opportunity has arisen for a talented graduate in a quantitative STEM, psychology, health or social sciences or related discipline to develop their data analysis and modelling
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offers the chance to work with zebrafish disease models, explore new therapeutic targets, and gain invaluable experience in experimental techniques such as CRISPR gene editing, in vivo imaging, and
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optimisation techniques and AI-based models to support decision-making in microgrid design and operation. Working in collaboration with a leading global mission critical firm of engineers, this project offers
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engineering or related discipline. Knowledge, Skills and ExperienceKnowledge of research methods relevant to urban resilience, infrastructure systems, Life Cycle Assessments or data-driven modeling. Proficiency
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evasion thus supporting bacterial pathogenesis. We will characterise the antibacterial and anti-host activities of the T6SS and selected effectors using in vitro and in vivo models, deletion mutants and
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evasion thus supporting bacterial pathogenesis. We will characterise the antibacterial and anti-host activities of the T6SS and selected effectors using in vitro and in vivo models, deletion mutants and
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fluctuate in line with business requirements. Our working model arrangements are a non-contractual benefit so please note that an Arden work location is added to our employment contracts. About Arden
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-source software packages. As a Research Assistant, your primary duty will be to support the analysis of real-world data mapped to the OMOP Common Data Model, contribute to wider project planning, including
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partners in Thailand and Australia in a project funded by the British Council, and you will be responsible for investigating the latest developments in computer vision and Deep Learning to develop powerful