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transition. This ambitious goal will be achieved by developing advanced experimental and computational tools to characterize e-fuel combustion processes, optimize fuel-flexible technologies, and integrate
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-169764OR-C22). The selected candidate will work in a multidisciplinary environment in the field of medicinal chemistry, molecular modelling and antiviral research. The project will involve the design and
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close collaboration with industrial partners worldwide. You can read more about the department at www.es.aau.dk. Your work tasks The PhD project will investigate wireless-native physical AI systems, with
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overall focus will be to strengthen the department’s expertise in closing the building “performance gap” through data-driven building operation optimization and system innovation. You will bridge advanced
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develop advanced models, algorithms, and control solutions for simulating, optimizing, and operating future integrated energy systems. We address the challenges arising from the increasing integration
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. The objective will be to determine the optimal correction strategies as a function of tissue type and imaging depth. A second objective will be to exploit this platform for organ-scale mapping of intrinsic label
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function approximation and optimal control. ● Contribute to writing scientific papers on the project results and assist in disseminating these results at conferences and workshops. The selected candidate may
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(ISCR), is to design electrochemical and optical tools to analyze this process, enabling determination of optimal conditions for surface functionalization. This will require the development of two new
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systems, optimizing audio playback levels, and supporting other acoustic interventions to improve occupant comfort and building performance. The research will adopt a human-centered approach, placing
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are optimized based on plant performance and energy price fluctuations. The learned models and resulting data-driven control approaches will be designed to be more easily transferable between different