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the section that aims to develop the next generation of scientists trained in bioinformatics, AI/ML and data science who have a deep understanding of experimental biology as well. Responsibilities As a PhD
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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these frameworks to develop specific formulations and solution algorithms for the design of congestion pricing schemes using classical transport models and quantify the equity-efficiency trade-offs for congestion
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will learn and adapt the realms of the combustion modes and fine tune the performance for each while the engine is operated. Self-tuning, adaptive, control algorithms will be used. This part of the three
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a highly interdisplinary projects where the PhD student will learn and develop skills in sustainable material design, membrane technologies, prospective life cycle assessment, and industrial
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microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM components are in use
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to Improve Current Density and Energy Efficiency in Redox Flow Batteries). SPACER aims to develop new architectures for porous electrodes to improve the power density and energy efficiency of redox flow
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cancer (SCLC). As part of the EU-funded MIPrecise network (Marie Skłodowska-Curie Actions Doctoral Network), you will develop and apply advanced mass spectrometry and nano–liquid handling workflows
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for Quantitative Sustainability Assessment of the Department of Environmental and Resource Engineering (DTU Sustain). The section spearheads the development of sustainability assessment methods. You will become part
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within the consortium. Provide data driven insights to guide the development of eco-friendly membrane technologies. Collaborating with fellow researchers across the UP2MEM network Participating in