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treatment processes through advanced machine learning, validated against physics-based models and experimental data. 2. System Integration: Integrating the DTs into material and energy balance equations
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models. This theoretical project will facilitate close collaboration with experimental groups and enable benchmarking of theoretical predictions. The PhD researcher will be part of the Correlated Quantum
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progression. This project addresses the challenge of studying early tumorigenesis in pancreatic cancer by developing advanced in vitro models based on human extracellular matrix (ECM), aiming to recreate
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and simulation techniques to reduce food waste and make food supply chains more sustainable? If your answer is “Yes!” to these questions, then this PhD position might be the perfect opportunity for you
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numerical modelling framework to simulate how light and heat interact with the target body tissue, while also incorporating neural signalling dynamics to explore how light-based stimulation affects
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reduces computational cost and enables large-scale reactor simulations, current porous approaches, based on Reynolds-averaged Navier-Stokes models, rely on empirical correlations and assumptions that may
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models at many scales including electron dynamics, soft-matter physics, materials-biomolecules interaction and device physics exploiting the collaboration with a multidisciplinary team of theoreticians and
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with regular waves. Extending the model to full two-way coupling, allowing feedback from flexible vegetation on wave-induced flow. Applying the fully-coupled model to simulate interactions under both
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(immersive reality, planning and simulation models) for joint planning assessment · support demonstrators of the developed prototypes in the project You will be part of a team comprising three PhD
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and heat transfer in geothermal systems under high-pressure and high-temperature conditions relevant to AGS. • Developing high-fidelity direct numerical simulation (DNS) models to map