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tracking and autoencoders for amplitude and phase noise characterization Bayesian filtering Building experimental set-ups for noise characterization Reinforcement learning strategies for comb generation
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focus on the following areas: Subspace tracking and autoencoders for amplitude and phase noise characterization Bayesian filtering Building experimental set-ups for noise characterization Reinforcement
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. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry. Responsibilities and qualifications
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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developing 3D vision algorithms for object detection, recognition, and scene understanding to support planning and task execution in dynamic environments. Publishing research findings in leading international
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institutions with the objective of receiving a doctoral degree (PhD). State-of-the art, exciting research in an international consortium with highly integrated research projects. Expert training in basic and
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project position is the design and numerical simulation of quantum-dot-based single-photon sources using advanced optical simulation tools. The objective of the PhD2 project is the microfabrication
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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offered in this context, with the objective of modelling, coding, and field-validating a new mechanistic analysis tool for pavements containing fungal-bound granular layers. The research will focus on urban
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collaborative research team and take responsibility for your individual research objectives. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and you will be enrolled in