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Computational modelling of chemical interactions in soil School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Natalia Martsinovich Application Deadline: Applications
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on-premise Microsoft SQL Server and Cloud/SAAS based systems which are central to the operation of the University. Leveraging this data to inform strategic decision making is critical to efficient operation
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will have substantial experience in practical research as well as statistical epidemiology, handling large (e.g. proteomics) and complex longitudinal datasets in a cloud-based platform. Excellent written
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, design, delivery and ongoing operation of Liverpool John Moores University’s enterprise data network across on-premises data centres and cloud environments. The role leads a team of specialist engineers
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methods. SQL and NoSQL databases. Big data technologies (e.g. Apache Spark or similar). Cloud-based data platforms (e.g. AWS, Azure, GCP). Building and deploying data analytics or machine learning solutions
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commitment and is the largest single investment in AHRC’s history. Opening at Pinewood Studios in 2026, CSNL will include state-of-the-art studio and stage facilities, advanced creative computing, AI, cloud
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computing, edge computing, distributed computing or cloud computing. Experience in real‑time applications and in developing research demonstrators is essential. You will be an effective communicator, able
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to undertake computing work at the cutting edge of Data Science. The post holder will be able to apply their skillset to advanced projects such as Cloud computing and enterprise architecture as well as work in a
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, design, delivery and ongoing operation of Liverpool John Moores University’s enterprise data network across on-premises data centres and cloud environments. The role leads a team of specialist engineers
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software stack from containerised backend systems of services running in kubernetes and cloud services, to adaptive front end XUI systems including state of the art AR and VR systems. You’ll be welcomed