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academic or industry leadership roles. Your profile Applicants should hold a PhD in Computer Science, Electrical Engineering, Computer Engineering, Telecommunications, or a similar field, with a strong
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identification, and who have significant experience in applying Machine Learning (ML) and Artificial Intelligence (AI) to these areas. Applicants with theoretical, numerical, experimental, or combined research
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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with troubleshooting their machines and support their understanding of core concepts. Guide students in working on their own project. Demonstrate best practices and foster the development
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thesis project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer
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); natural language processing (NLP); machine translation. Modelling and measurement: statistical modelling; supervised machine learning; measurement and validation for formative and reflective constructs
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position A PhD degree or equivalent in history, classical studies or related research areas. Documented experience with research on and teaching digital methods. Experience with didactic integration
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Policy Implications and Recommendations Case Studies of Successful Innovation Funding Methods The project will employ a combination of methods, including machine learning (ML) and generative AI (GenAI
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. Supervising student projects and theses, particularly within converter technologies, electrolysis integration, and power system stability. Successful candidates should have a PhD in electrical engineering or a
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programmes across Arts. Qualifications for the assistant professor position A PhD degree or equivalent in history of ideas, philosophy or related research areas. Documented experience with research on and