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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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connection to the project context Disseminate results through scientific publications in outlets on the intersection between computer science, power engineering and information systems Support the
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, it is a prerequisite that you gain admission to the PhD programme in Engineering within three months of your employment contract start date, and that you participatein an organized doctoral programmet
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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, engineering (e.g.: mechanical, electrical, electronic, materials) or a related subject. A relevant master’s degree and/or experience in the use of wearable technology will be an advantage but not essential
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Full-time enrolment in a PhD program at Curtin University Background in artificial intelligence, computer vision, or structural/civil engineering Demonstrated research experience, with evidence of
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As Austria's largest research and technology organisation for applied research, we have set ourselves the goal of making substantial contributions to solving the major challenges of our time
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PhD project: 3D-Printing Devices with Responsive Structural Colour Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive
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select *Loughborough* and select the programme ‘CDT Engineering Hydrogen Net Zero’. Please quote the advertised reference number *LU-EnerHy-2025-3* under the ‘Finance’ section of the application. To avoid
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Location: UK Other Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM