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on information theory, machine learning, and control to analyse how local variability, sensor drift, and platform differences affect both global model performance and human supervisory factors such as workload and
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7 Aug 2026 Job Information Organisation/Company Sofia University "St. Kliment Ohridski" Department FEBA Research Field Computer science Engineering » Computer engineering Information
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-Physical Energy Systems The PhD position focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be
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learning, computer vision, or a related field; knowledge of affective computing, generative AI models, and deep-learning methods; proficiency in Python and experience with machine-learning libraries
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problems, numerical mathematics, optimisation, machine learning and imaging physics, with applications ranging from medical and industrial imaging to geophysics. For more information, please visit
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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even makes room for good conversations over high-quality tea. Job description As a PhD candidate, you will contribute to cutting-edge research on next-generation wireless communication and sensing
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backgrounds such as AI, computer vision, computer graphics, machine learning, robotics, wearable technologies, textile engineering, fashion technology, digital fashion, or related areas are encouraged to apply
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an unnecessary discarding of generated power. This four year’s PhD position is aimed at using captured CO2 from point sources and hydrogen from water electrolysis to generate carbon-based base chemicals and fuels
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and economic use of renewable electricity without an unnecessary discarding of generated power. This four year’s PhD position is aimed at developing multiphase models to predict the dynamics and