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Job Description DTU Chemical Engineering is seeking a highly motivated PhD student to work on pilot-scale CO2 capture, CO2 quality assessment, and development of innovative solvent systems
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for optimizing metals 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
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degradation modes. Evaluating suitable sensor technologies and data sources for acquiring relevant metrics. Developing tools and algorithms to automatically analyse sensor data, assess asset condition, and
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potential market failures and prevention mechanisms. You will be combining theoretical analysis with practical applications, involving mathematical modeling, algorithm development, and coding. You should have
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will focus on developing a bioinspired, AI-driven BCI system that enables intuitive and adaptive control of a wearable wrist-hand exoskeleton for stroke rehabilitation. The system will integrate
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data Design algorithms for correlating low-level events into process-level attack models Contribute to joint framework development with TU/e on continual learning Collaborate with industry partners
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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 take advanced courses to build and deepen your skills, implement and evaluate algorithms, and develop your ability to write and present scientific work. We are a supportive team that will welcome
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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