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Job Description If you have solid practical experience in embedded systems, computer engineering, or related areas — and are excited to teach, collaborate, and shape the next generation of engineers
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Job Description Are you a highly motivated scientist with an interest in computational approaches to strain design? Do you have a fundamental understanding of microbial molecular biology and
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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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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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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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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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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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: You will be responsible for the sensor system and the perception algorithms of an autonomous mobile robot. You will engage in research around deep learning and 2D/3D computer vision for a well-defined
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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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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of