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Field
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: 30 August 2025 Apply now As part of the EMBRACER project external link , you will use advanced models integrating our climate system to human behaviour to study potential scenarios of what could happen
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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/Simulink/Python for modelling, simulation, and control design. Experience with genset systems, hybrid powertrains, or real-time control applications is highly desirable. A practical interest in system
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with researchers from climate physics, hydrology, sustainability science and complex systems dynamics and apply a range of different models. Starting from the recent AMOC tipping simulations performed
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aims at developing tools using large language models (LLMs) for the correction of misinformation about climate change in social media. The successful candidate will develop innovative tools leveraging
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, engineers and PhD candidates. The PhD candidate is expected to develop an advanced engineering noise prediction model for efficient computation of sound propagation in a range-dependent atmosphere where
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computing. Current challenges in quantum technology adoption stem from the lack of standardized benchmarking methods and the inherent difficulty in validating quantum devices beyond classical simulation
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process