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the School of Computer Science at the University of Sheffield, you will lead the machine learning research on acoustic foundation models for respiratory health. You will work with large-scale real-world
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Digital manufacturing, Industry 4.0, or cyber-physical systems o Product design for disassembly, remanufacturing, or recycling o Data analysis, AI, or machine learning applied to engineering systems
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at Saxion University of Applied Sciences, you will contribute to the development of machine-learning models that connect powder characteristics and process parameters with the properties of the final
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to think independently, in human-AI interaction. You will connect the project's technical work with its grounding in cognitive theory. The position suits candidates with a PhD in Human-Computer Interaction
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, quantitative image analysis, data processing and machine-learning-based modelling. More about the position The main purpose of the fellowship is research training leading to the successful completion of a PhD
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changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network
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, or a comparable degree relevant to the PhD specialisation in Communication. Relevant disciplinary backgrounds include, but are not limited to, communication, media studies, human-computer interaction
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dedicated researcher with a PhD in mathematics, electrical or mechanical engineering, computer science or a related field, and a strong methodological background in machine learning. The ideal candidate has
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).The PhD candidate is expecting to assisting in teaching and help in laboratory on the related topic. Applicants should fulfil the following requirements: A Master's degree in computer engineering, computer
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interface of machine learning, deep learning, data science and applications in forest sciences. Together with the Director, you will further develop KIForst as a faculty-wide platform for methodological