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processing power of a novel photonic integrated circuit architecture [Heuck2023]. This includes studying the effects of optical loss and decoherence and methods to overcome these by error detection and
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electrolysis Design of electronic circuits and power electronics Materials characterization Electrochemistry Moreover, the successful candidate is innovative and able to work in cross-disciplinary teams has good
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rehabilitation. It aspires to lay the groundwork for integrating these systems into modern healthcare infrastructures, enhancing the quality, accessibility, and continuity of care for aging populations
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to material, cutting tools and parts production. The PhD project will therefore focus on the development of an integrated system combining direct and indirect tool wear monitoring for reliable residual life
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bottlenecks in data and system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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an efficient AI foundational exploration of the molecular space. How can we bias the generative models towards desirable molecular properties How can we integrate generative AI models and different molecular
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conceptual framework linking nanoscale features to macroscopic adsorption efficiency. Generate and curate high-quality datasets to support data-driven materials optimization and future integration with AI
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Engineering, section for Fluid Mechanics, Coastal and Maritime Engineering. The PhD project will play an integral part of the project “Marine advection and dissipation in the vegetated coastal environment