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global network of campuses and partners for students and faculty to leverage for learning and research; a deep investment in lifelong and experiential learning; a premium placed on pedagogical innovation
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the Norwegian educational system The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ All
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the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres of technology, economy and our everyday life. Machines perform comparably to, or even surpass
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experts who combine technical excellence with a deep understanding of sustainable development in shaping societies. Our research focuses on sustainable built environment, mechanics and materials
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, or related background. Strong background in machine learning, computer vision, and deep learning. Knowledge of transformer architectures and foundation models. Experience with few-shot learning, self
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and ability to work both independently and collaboratively Experience with deep learning frameworks, such as Tensorflow or Pytorch is advantageous Experience in numerical methods for partial
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translational medicine concepts Publication history in relevant fields (AI/ML, genetics, toxicology) Experience with deep learning frameworks and generative AI models (e.g., GANs, VAEs) Key Leadership
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at appointment. See the following table for the salary scale for this position https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-july-2025-scales/t15.pdf . A reasonable estimate for this
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop
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redesign. Required Qualifications: • PhD in Statistics, Mathematics, or Data Science awarded by August 2026 • Ability to teach a wide variety of mathematics and statistics courses within the current