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of forests in climate change are now key social issues that require more knowledge. In order to both sustainably use and safeguard forest biodiversity, a coherent basic science research program is needed
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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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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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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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, 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
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in engineering, computer science, physics, or degree program with similar technical focus Experience with radar/microwave remote sensing data and instrumentation Knowledge of a scientific programming