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engineering or related field At least 1 year of relevant experience in signal processing and machine learning. Good written and oral communication skills Proficiency in ANSYS, and lab test skill Ability to work
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duties as assigned. REQUIREMENTS: REQUIRED: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong programming skills. Strong background in machine
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. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Deep Learning for Medical Imaging and Multi-Modal Data in
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machine learning, spatial audio and audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate generative audio AI technology for production
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of the researchers of the DKM group are also affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) . The candidate is expected to join Integreat and strengthen the interdisciplinary
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superlattices (twistronics). The role will focus on developing and applying theoretical models and computational quantum chemistry and machine learning methods to uncover novel properties and phenomena in low
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conducting quantitative analyses or master game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement
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convergence of high-performance computing (HPC) and AI, which is a subject that sees an increasing importance due to the widespread use of AI and in particular machine learning (ML). As today’s mainstream AI/ML
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. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Deep learning for imaging of marine ecosystems Apply
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advanced statistical and machine learning modeling to conduct data analyses for large-scale multimodal (genomics, omics etc) studies. Conceptualise new ideas, lead data-driven discoveries, ensuring in-depth