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Field
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printed circuitry with custom microfabricated bioresorbable sensors, this device will be tested in a simulated intestinal environment. The device will have three separate lifetimes, the structural lifetime
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PROCEDURE FOR DRAWING UP OF PREDOCTORAL CONTRACTS FOR THE TRAINING OF DOCTORAL STUDENTS FUNDED
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life cycle by: Reducing material usage during manufacture. Improving electrical system efficiency and power-to-weight ratios during operation. Enhancing recyclability and resource recovery at end of life
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research exploring the processes controlling tropospheric composition (gases and particles) and their intersection with global change. Research makes extensive use of global modeling tools (GEOS-Chem and
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material models, the development of Digital Twins, and the use of AI-based methods. This includes building model-ready databases, developing simulation chains that link process simulations with analysis
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PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High Velocity Impact
11th October 2026 Languages English English English The Department of Structural Engineering has a vacancy for a PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High
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modeling, computer simulation, non-linear model analysis, interactive learning environments and decision-laboratory experiments. About the project/work tasks: Description of the INTEGRATOR project
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2 PhD Positions in Computational Modelling of Biological Membranes and Adaptive Functional Materials
simulations and explore large parameter spaces. The project is particularly suited for candidates interested in statistical physics, computational physics, stochastic processes and theoretical condensed matter
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filters and observers, for real-time applications. Proficiency in MATLAB and Simulink for modelling, simulation, and validation using experimental or real-world data. Strong analytical, independent research
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while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed