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Kingston University has developed and pioneered the use of innovative technologies in recent years that we hope will have a significant impact on the space and launch propulsion sectors building
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they will have to do a research secondment at GE Vernova. Essential Requirements: Applicants should have a first-class Master’s degree (or other equivalent experience). The successful candidate will have an
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lines and collect high-throughout measurements of corresponding mRNA and protein levels for several protein targets. Ultimately, you will use these data to develop Matchmaker, a machine learning framework
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understanding of flood risk and its impact, alongside tools that assess the effectiveness of management solutions, to inform decision making and policy recommendations. This project will use the CityCAT model
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. Equal opportunities for all: We welcome every additional/new personality to the team! Employment duration: The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship
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(CAD) since 2016 and CT- Fractional Flow Reserve (CT-FFR) as a second line test since 2017. In 2018 a national health technology programme funded CT-FFR utilisation with the aim of improving patient
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engineering/science, remote sensing, computer science). A relevant master’s degree and/or employment experience will be an advantage. English language requirements: Applicants must meet the minimum English language
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of work as a case study. The candidate will develop a practice-based methodology to analyse, critique and respond to the living history of the company, resulting in the creation of taxonomical scores
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to be able to screen all FOXA1 amino acids, using saturation mutagenesis screens, in order to identify amino acid residues that are important for FOXA1 to function. We aim to use this approach
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the potential to use that knowledge to design new drugs, new biomaterials or to identify new therapeutic opportunities. What You’ll Do You will receive training and hands-on experience in: Investigating how