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qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
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subject. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability
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related subject. Proven experience with X-ray imaging techniques, e.g. µCT, nanoCT, TXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability to work both
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and academic disciplines. The Academy is also home to the Lindblad Studio, an experimental laboratory for sound, media, music technology and computer-assisted composition. More about the Academy
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of your thesis. Experience of working with optimisation methods, long-term modelling of the forest landscape and its ecosystem services, as well as computer-based decision support systems in general
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and promotion of teachers and appointment to docent,” available in Section “Instructions to applicants” at: https://www.bth.se/eng/about-bth/vacancies Meriting competencies and experience In
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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industrial secondments within Europe. Requirements To meet the general entry requirements for doctoral studies, you must: hold a Master’s (second-cycle) degree in electrical and computer engineering
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well as within security for critical infrastructure. More about research and eduction in cybersecurity at Linköping University is found here: https://liu.se/en/research/cybersecurity As Assistant professor in