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. On the computational side, the project includes calculation of established and novel structural parameters that can be linked to the experimental data. The candidate is expected to be able to interpret and present
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collection parameters for automated analysis pipelines; developing, optimising and implementing AI/ML workflows and validating analysis using physico chemical approaches. The research will be in close
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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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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