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Luleå University of Technology seeks a driven and committed PhD student with a focus on the effects of climate change and different adaptation measures on urban streams. Take the opportunity to join one
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 18 hours ago
The PhD programme is open to national and international students who hold a Master's degree or equivalent in Environmental Science, Environmental Engineering, Environmental Economics, Environmental
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practical knowledge and skills in cutting-edge information technologies. Focusing on innovation and experiential learning, we prepare students at all levels, including PhD, Master, and undergraduate
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federated learning, AI security and privacy, quantum machine learning (QML), robotics, and/or AI-driven discovery in science and engineering (e.g., genomics, bioinformatics, drug discovery, infectious disease
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, Lei Zhao, Mahendra Bhandari, Unmanned aerial system and machine learning driven Digital-Twin framework for in-season cotton growth forecasting, Computers and Electronics in Agriculture, Volume 228, 2025
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of postdoctoral associates, PhD students, and several Master’s or undergraduate students across multiple universities and organizations. The research team will work alongside the engineering team to investigate
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experimental workflows for generating and automating the acquisition of high-quality training datasets for machine learning models. Provide training to students on new technologies, protocols, and best practices
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reliability. Prospective applicants for this PhD proposal should have the following qualifications: M.Sc. degree in communications engineering, mathematical engineering, electrical engineering, computer
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familiar with data science and machine/deep learning toolkits. Experience with model deployment and the usage of MLOps tools (Dockerization, CI/CD pipelines, edge infrastructure, etc.) is a plus. As a PhD
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computer science/statistics/applied mathematics/electrical engineering can also be considered given that the candidate has formal competence in machine learning and/or image analysis/computer vision Foreign