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and development of associated sensing and estimation algorithms Path planning based on medical imaging data (e.g., MRI, CT, angiography) Development of AI-based control methods for continuum robots
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will: Develop and implement model-based and data-driven (AI) optimization algorithms for battery charging Integrate physics-informed models and data-driven tools to design health-aware charging protocols
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: Implement and optimise deep learning–based models for the quality control and real-time assessment of concrete constituents within in-line production. Develop and train predictive algorithms based
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is to develop machine-learning-based algorithms for transmitter pre-distortion and receiver post-distortion architectures that enable distortion-free quantum communication systems. A key focus will be
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on stability. Testing the model in standard stirred tank apparatus Refining the model to allow predictability between different types of apparatus. Defining an algorithm for testing enzyme stability
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simulation tasks. A key objective will be the development and testing of algorithms for gas hydrate phase equilibrium calculations. CapSim seeks to advance CO₂ capture simulation technology by enhancing
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describing the effect of conditions on stability. Testing the model in standard stirred tank apparatus Refining the model to allow predictability between different types of apparatus. Defining an algorithm
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to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life-science-relevant chemical and
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approaches, such as topology optimization, with gradient-free methods, such as genetic algorithm, in order to exploit the specific strengths of the two classes of algorithms, and through this reach an ideal
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and communication systems. You will work with real measurement data and participate in both algorithm development and experimental validation. You will collaborate with industrial and academic partners