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Admission to Doctoral (PhD) Studies in the subject Engineering Sciences with specialization in Biomedical Engineering at the Division of Biomedical Engineering, Department of Materials Science and
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application! We are looking for one or two PhD students in Multiagent Automatic Control at the Information Coding Division (ICG), which is based at the Department of Electrical Engineering (ISY). You will be
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to fields such as critical theory, digital sociology, criminology, or science and technology studies (STS). As part of the application, the doctoral student will draft a brief plan for an independent project
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bioinformatics, engineering physics, molecular biology, computer science, or a related field. You should have strong programming skills (e.g., in Python or R) and a keen interest in applying data-driven methods
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: The successful candidate must have a Master's degree in electrical engineering, engineering physics, or related disciplines. Completed courses in signal processing, radar or communication theory are meritorious
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computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel the anthropogenic and natural processes, and their relative
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engineering, computer science, physics engineering, or equivalent) Programming skills in Python or another language Strong work ethic Fluency in English, with the ability to write, communicate, and interact in
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departmental duties, up to a maximum of 20% of full-time. Your qualifications You have a Master’s degree in electrical engineering, engineering physics, computer science, applied mathematics or have completed
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, up to a maximum of 20 per cent of full-time. Your qualifications You have graduated at Master’s level within the civil engineering courses such as technical biology, chemical biology, biotechnology, a
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big