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will work on cutting-edge projects related to coastal and ocean wave modelling using Delt3D software. The role of the researcher is to perform physics-based modeling to build a numerical model that can
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to provide support on the application and interview process. Discover our benefits, visit Your Benefits website. We welcome applications from UK, Europe and worldwide and aim to make your move to the UK as
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to provide support on the application and interview process. Discover our benefits, visit Your Benefits website. We welcome applications from UK, Europe and worldwide and aim to make your move to the UK as
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development programmes. The fellowship is tenable for one year. On an exception basis, a two-year programme may be supported. Service Commitment One year for every year of sponsorship. Application Process
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-level research fellow on a fixed-term basis in the field of thin film materials design and coating growth by physical vapour deposition. The successful candidate will have considerable experience with
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The application process begins on Tuesday 25th August 2026. The application must be submitted through the website by 5.00pm on Friday 25th September 2026. No applications will be accepted after
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into many novel aspects of developing offshore digital twins, such as sensing, data handling, physics and AI modelling, software development, as well as experiments at the Cranfield Ocean Systems
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Inverse Methods and Ionospheric Modelling Research Fellow - School of Engineering - 106995 - Grade 7
Job Description Position Details College of Engineering and Physical Sciences Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,636
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support for the site PI and the wider DISCA research team if required. Candidates must have (or be in the process of completing) an MSc degree in Psychology or a mental-health related area and have some
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process evaluation of Future Skills implementation, examining contextual enablers and barriers to success - Contribute qualitative insight to quantitative longitudinal research, capturing evidence on skills