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PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High Velocity Impact
work. Some experience in modelling of composite materials. Some experience in programming (Python, Fortran, CUDA or similar). Some experience in fluid mechanics and biomechanics. Personal characteristics
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work; Experience with data analysis, such as statistics, data management, etc.; Experience in scripting/programming (e.g., R, Bash, Python); Strong interest in understanding human impacts on ecological
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Python, MATLAB, R or equivalent You must have relevant knowledge or experience in one or more of the following: railway engineering, infrastructure maintenance, rolling stock, condition monitoring, sensor
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must have excellent written and oral English skills You must have good programming and data-analysis skills, for example in Python, MATLAB, R or equivalent You must have relevant knowledge or experience
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, enabling new approaches for cancer treatment. A central challenge is to understand and control how different nucleic acids are co-encapsulated within a single nanoparticle and how their organization affects
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-ahead, intraday, and balancing markets to maximize socio-economic value while respecting system security and reliability constraints. Different approaches can be explored, such as integrating
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: Design, implement and characterize innovative sensing systems based on different sensing principles such as ultrasonic, optical and chemical sensors. Investigate sensor behavior under varying environmental
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, or Python. The studentship covers fees at Home rate (UK and EU applicants with pre-settled/settled status and meet the residency criteria). International applicants must cover the difference between Home and
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Agency funded BILMo (Biodiversity Inspired Lake Modelling) project, which aims to upgrade different mechanistic lake models to 1) predict diversity and community composition responses to combined gradients
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that generalize across different physical settings. Building on this motivation, the project focuses on the definition, development, and analysis of scientific foundation models: large-scale, generalizable models