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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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happy to discuss this opportunity via email s.calnan@lboro.ac.uk . Supervisors: Name of primary supervisor: Prof Sonya Calnan Name(s) of secondary supervisor: Dr Sarah Dunnett Entry requirements: Subject
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Engineering, Physics or Materials Science Excellent English written and spoken communication skills The following skills are also highly desirable: Ability to program in Matlab, Python or similar Strong
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equitable. This UKRI Frontier project was selected for funding by the European Research Council (ERC) and is led by Prof. Anna Korhonen. The goal of the project is to investigate the challenges in
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glycosylation, the most complex cellular enzymatic process chemical or chemoenzymatic synthesis of glycan-based reporter molecules and small molecule inhibitors contribution to scientific primary publications
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university education (bachelor and master programme) was English, or; – scoring at least 100 on the TOEFL iBT test or 7.5 on the IELTS test. Two (academic) reference letters, preferably from a thesis
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Award duration: 4 years Food processing currently relies heavily on the combustion of natural gas to provide process and space heating. Until recently, natural gas was considered the preferred fuel
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element modeling, computational fluid dynamics). Knowledge of heat and mass transport processes in heat-sensitive materials and process optimization. Experience in supply chains and hygrothermal
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general enquiries on the scholarships, please email: Research Programme Leader, Dr Irma Malafronte, at irma.malafronte@roehampton.ac.uk For administrative support regarding the application process, please
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modelling. Application of the produced soft sensor to investigate the feasibility of process control. The project will be supervised by Prof. Jürgen Hubbuch and Dr.-Ing. Iris Perner-Nochta. The successful