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Field
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candidate will have a PhD in a strongly quantitative discipline, but applications from candidates close to submitting their PhD are also welcome. Familiarity with deep learning methodologies is essential, as
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Science or related discipline, together with demonstrated experience in Foundation Models (generative AI), as well as Bayesian machine learning, ML security, or general deep learning, a documented track record of
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implement cognitive attention models for computer vision adapted to event data. A first step will be to study the state-of-the-art attentional mechanisms in deep networks and their link with cognitive
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student This doctoral research project focuses on decoding the regulatory grammar in the RNA that control cell-type specific alternative splicing. Deep learning models are making great advances in society
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Python programming and familiar with deep learning frameworks such as PyTorch and TensorFlow. Preferred experience includes presenting or preparing scientific manuscripts for journals or conferences. How
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. Primoz Skraba, to bridge the gap between topology and deep learning by investigating how stochastic topological tools can be developed and used to systematically analyse, interpret, and improve
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Degree or equivalent Research FieldChemistryEducation LevelBachelor Degree or equivalent Skills/Qualifications 1. Research experience coupled with proficiency in deep learning programming (e.g., Fortran
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are holding a PhD/DPhil in Computer Science or related discipline, demonstrated experience in Foundation Models (generative AI) as well as Bayesian machine learning, ML security, or general deep learning, a
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Intelligent Systems, in particular, fuzzy systems, evolutionary algorithms, edge computing, tinyML, deep learning applied to computer vision, and data science and big data with Apache Spark. LanguagesENGLISH
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for science, with scalable modern methods, interdisciplinary expertise and industrial-scale computation. A solid background in deep learning is required, including some published work. Expertise in Earth system