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fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and results
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our team at DTU Compute, offering a fully funded position within a dynamic and interdisciplinary research environment. The positions are part of the research project “AI-driven materials optimization
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for application in biocatalysis. Enzyme kinetic analysis. Development and optimization of multi-enzyme cascade reactions. Disseminating project results through scientific publications and conference presentations
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collaboration. We also provide active support for developing courses, securing research funding (Danish and EU), and building a strong professional and academic network. Responsibilities You will co-lead the
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-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus. Excellent communication and collaboration skills across disciplines. We offer DTU is a leading technical university
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Post Doctoral Researcher in Digital Twins CO2-to-Protein production in collaboration between the ...
regions of the world, and at the same time impact the climate positively utilizing CO2 as raw material. To be launched into scaled solutions, the technology needs to be optimized through leveraging digital
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regions of the world, and at the same time impact the climate positively utilizing CO2 as raw material. To be launched into scaled solutions, the technology needs to be optimized through leveraging digital
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contribute to other educational activities Attract research funding with support from the department Disseminate your work at conferences and peer-reviewed journals Network with international research bodies
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chemical–biological pathway. The advertised positions will support these efforts through research on advanced carbon capture methods, process modelling and optimization, and biological CO2 valorization in
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will work with data collected from the field to the spatial scale, and investigate spatial optimization approaches to improve the model parameterization at the spatial scale. We expect that you will be