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models Use of PyTorch and/or HuggingFace ESSENTIAL REQUIREMENTS To be registered as a student in an undergraduate master’s degree programme in Computer engineering, Computer Science or a cognate
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DFT, beyond-DFT, and experimental techniques. We are also interested in developing both forward and inverse machine learning models to accelerate and optimize the design processes. We work in close
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learning models on wearable electronic circuits, devices, and platforms, with particular emphasis on smart eyewear. The research activities will address multiple application domains, including embedded
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We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a Pre-Doc Specialist position in the Robotics
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research into practical, scalable solutions for modern dairy farms. We develop machine learning models, decision-support tools, and digital platforms that improve production efficiency, herd health
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present. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python skills, preferably some
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large
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Science, or related field Knowledge of flexible antennas, wireless communications, and machine learning Good skill set in signal processing and optimization techniques Proficiency in Python for modeling and machine
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applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata. Build and evaluate monocular depth pipelines
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse