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resilience. Experience with advanced modelling techniques for logistics and supply chain analysis (e.g., simulation tools, digital twins, or data-driven optimisation methods). Knowledge of food quality and
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combines leading expertise and unique know-how in theory, modelling, synthesis, atomic-scale imaging and spectroscopy, and nanoelectronics aiming to unlock the potential of AlN and UWBG materials for next
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models of interacting ecological and evolutionary (eco-evolutionary) processes. You will conceptualize and model the complexity in which ecological divergence and speciation drive an adaptive radiation
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thermal conductivity b) Development of hBN thermal interface material that combines a high degree of compressibility and recovery c) Modeling, simulation and characterization of phonon transfer across
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of cybersecurity and AI, i.e., attacks and defenses leveraging AI solutions, or attacks and defenses within AI solutions (e.g., backdooring, model poisoning, membership inference), cybersecurity of generative AI
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, and false positive detection, which is particularly important for fainter sources. An additional aspect is multi-messenger science and we wish to investigate the use of external data (e.g. from Gaia
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knowledge of the underlying association models. Demonstrated pedagogical skills. Additional assessment criteria: Consideration will also be given to good collaborative skills, drive and independence, and how
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data collection, integration, and modelling and 2) co-constructing case studies to demonstrate how this workflow may be applied at the local scale but also integrated internationally. This postdoc
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science-related applications. Explicitly accounting for symmetry is not the standard approach in machine learning – a well set up model should be able to ‘detect’ the symmetry automatically. One way
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with a human-centric, sustainability-driven approach. The Postdoctoral researcher will work on using AI-powered methods, testing, and simulation technologies for the verification and validation