43 distributed-algorithm-"Fraunhofer-Gesellschaft" positions at Technical University of Denmark in Denmark
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Job Description The aim of this PhD project is to investigate the immediate and long-term deformation behaviour of plain and fiber-reinforced concrete using distributed fibre-optical sensing (FOS
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to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies. This is an exciting
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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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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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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for Science & Technology (KAIST), and an external stay at KAIST will be included as part of the PhD program. Qualifications Proficiency with Python Experience implementing various Machine Learning algorithms
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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agricultural robotics and new sustainable farming practices. The PhD projects will be combining new sensor systems and perception algorithms. So, if you are one of the 2 selected applicants, your primary