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related discipline. Good programming skills (e.g., Python, PyTorch, TensorFlow). A genuine interest in pushing the boundaries of efficient and deployable AI. Prior research experience (e.g., project work
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. Desirable Skills (an advantage, not a requirement) Data analysis skills in python. An interest in energy policy / the economics of energy. Numerical modelling. Eligibility This studentship is available for UK
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/teaching experience. The confidence to deal with uncertainty and tackle any problem without a defined final answer. Desirable Skills (an advantage, not a requirement) Data analysis skills in python. Granular
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such as Matlab and/or Python. How to apply Please send an email with subject “PhD studentship: Numerical simulation of boiling flows for high heat flux fusion components” to Dr Mirco Magnini, mirco.magnini
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. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in 2D convolutional neural networks in Python. This is a part-time position (5
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2D convolutional neural networks in Python. This is a part-time position (5 hours/week) funded until 31/03/2026 with a possibility of extension and is suitable for a Ph.D. student with relevant
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languages (Python/MATLAB) commonly used in machine learning applications, is desirable but learning can be completed during the PhD. Excellent communication and interpersonal skills to facilitate
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/robotic systems Ability to implement control and kinematics with hardware-in-the–loop Background with relevant packages, (MATLAB, SolidWorks/Creo, ROS/ OpenCV/ python, LabVIEW/C languages) A driven
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to implement control and kinematics with hardware-in-the–loop ◾Background with relevant packages, (MATLAB, ROS/ OpenCV/ python, LabVIEW/C languages) ◾A driven, professional and self-dependent work attitude is