
Ocean Science Consulting
Ocean Science Consulting
1 Projects, page 1 of 1
assignment_turned_in Project2019 - 2028Partners:Royal Bank of Scotland Plc, NHS Health Scotland, WEST Beer, NHS NATIONAL SERVICES SCOTLAND, Ofgem +82 partnersRoyal Bank of Scotland Plc,NHS Health Scotland,WEST Beer,NHS NATIONAL SERVICES SCOTLAND,Ofgem,nVIDIA,Dassault Systemes Biovia Ltd,Dassauly Systemes BIOVIA,NTNU (Norwegian Uni of Sci & Technology),NHS National Services Scotland,NatureScot,McLaren Applied Technologies,IBM Research,Royal Bank of Scotland Plc,University of Edinburgh,Duke University,Brown University,Cresset BioMolecular Discovery Ltd,National School of Bridges ParisTech,Intel UK,NM Group,WEST Beer,National Wildlife Research Institute,NPL,The Data Lab,James Hutton Institute,BioSS (Biomaths and Stats Scotland),TU Wien,Forestry Commission UK,Technical University of Denmark,AkzoNobel UK,DTU,CRESSET BIOMOLECULAR DISCOVERY LIMITED,uFraction8 Limited,Intel Corporation (UK) Ltd,Ofgem,Berlin University of Technology,The Data Lab,NERC British Geological Survey,AkzoNobel,James Hutton Institute,National Physical Laboratory NPL,uFraction8 Limited,Moody's Analytics UK Ltd,Brainnwave Ltd,Brown University,SNH,Utrecht University,British Geological Survey,Infineum UK Ltd,Oliver Wyman,Oliver Wyman,Aberdeen Standard Investments,PROCTER & GAMBLE TECHNICAL CENTRES LIMITED,National School of Bridges ParisTech,Norwegian University of Science and Technology Science and Technology,AkzoNobel UK,Norwegian University of Science and Technology,Ocean Science Consulting,OpenGoSim,Forestry Commission England,UNITO,Technical University of Denmark,Procter & Gamble Limited (P&G UK),THE JAMES HUTTON INSTITUTE,Johnson Matthey Plc,TUW,Leonardo MW Ltd,National Wildlife Research Institute,IBM Research,Aberdeen Standard Investments,BioSS (Biomaths and Stats Scotland),nVIDIA,Vienne University of Technology,Johnson Matthey plc,DEFRA,Johnson Matthey,TU Darmstadt,Moody's Analytics UK Ltd,Ocean Science Consulting,UP,Duke University,Infineum UK,OpenGoSim,NM Group,Brainnwave Ltd,McLaren Applied TechnologiesFunder: UK Research and Innovation Project Code: EP/S023291/1Funder Contribution: 6,384,740 GBPThe Centre for Doctoral Training MAC-MIGS will provide advanced training in the formulation, analysis, and implementation of state-of-the-art mathematical and computational models. The vision for the training offered is that effective modern modelling must integrate data with laws framed in explicit, rigorous mathematical terms. The CDT will offer 76 PhD students an intensive 4-year training and research programme that equips them with the skills needed to tackle the challenges of data-intensive modelling. The new generation of successful modelling experts will be able to develop and analyse mathematical models, translate them into efficient computer codes that make best use of available data, interpret the results, and communicate throughout the process with users in industry, commerce and government. Mathematical and computational models are at the heart of 21st-century technology: they underpin science, medicine and, increasingly, social sciences, and impact many sectors of the economy including high-value manufacturing, healthcare, energy, physical infrastructure and national planning. When combined with the enormous computing power and volume of data now available, these models provide unmatched predictive tools which capture systematically the experimental and observational evidence available. Because they are based on sound deductive principles, they are also the only effective tool in many problems where data is either sparse or, as is often the case, acquired in conditions that differ from the relevant real-world scenarios. Developing and exploiting these models requires a broad range of skills - from abstract mathematics to computing and data science - combined with expertise in application areas. MAC-MIGS will equip its students with these skills through a broad programme that cuts across disciplinary boundaries to include mathematical analysis - pure, applied, numerical and stochastic - data-science and statistics techniques and the domain-specific advanced knowledge necessary for cutting-edge applications. MAC-MIGS students will join the broader Maxwell Institute Graduate School in its brand-new base located in central Edinburgh. They will benefit from (i) dedicated academic training in subjects that include mathematical analysis, computational mathematics, multi-scale modelling, model reduction, Bayesian inference, uncertainty quantification, inverse problems and data assimilation, and machine learning; (ii) extensive experience of collaborative and interdisciplinary work through projects, modelling camps, industrial sandpits and internships; (iii) outstanding early-career training, with a strong focus on entrepreneurship; and (iv) a dynamic and forward-looking community of mathematicians and scientists, sharing strong values of collaboration, respect, and social and scientific responsibility. The students will integrate a vibrant research environment, closely interacting with some 80 MAC-MIGS academics comprised of mathematicians from the universities of Edinburgh and Heriot-Watt as well as computer scientists, engineers, physicists and chemists providing their own disciplinary expertise. Students will benefit from MAC-MIGS's diverse network of more than 30 industrial and agency partners spanning a broad spectrum of application areas: energy, engineering design, finance, computer technology, healthcare and the environment. These partners will provide internships, development programmes and research projects, and help maximise the impact of our students' work. Our network of academic partners representing ten leading institutions in the US and Europe, will further provide opportunities for collaborations and research visits.
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