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for a highly motivated and qualified PhD student/researcher who will work towards developing new (machine learning and deep learning-based) algorithms and procedures that exploit human labelling and
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are invited for two fully funded PhD studentships in Computer Vision and Machine Learning on the topic of Detailed Video Understanding. The aim is to go beyond the coarse-grained labels that current models can
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to identify trends in the data. Applicants should have a PhD in physics, materials science, electrical engineering, or a related field. A deep understanding of device physics, numerical modeling, and computer
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current drift-diffusion modeling software, applying it to experimental data, and using machine learning to identify trends in the data. Applicants should have a PhD in physics, materials science, electrical
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and prediction . PhD3 / RT3: Stochastic modelling and reliability assessment Job requirements A MSc degree in Computer Science, Data Science, or related fields A strong background in deep learning
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electromagnetic modeling techniques are required and deep theoretical insight into electromagnetic fields and computational methods will be the key ingredients of this PhD research. The project will be caried out
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in computer science, software engineering, or electrical engineering. You possess excellent programming skills in Python and have experience with deep learning frameworks. You also have experience or a
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techniques are required and deep theoretical insight into electromagnetic fields and computational methods will be the key ingredients of this PhD research. The project will be caried out in close
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modeling techniques are required and deep theoretical insight into electromagnetic fields and computational methods will be the key ingredients of this PhD research. The project will be caried out in close
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Computer Science, Data Science, or related fields A strong background in deep learning, distributed ML, and AI model optimization Good scientific programming skills and experience inlanguages such as Python