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Field
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networking and collaborations are regarded as an integral part of the PhD research experience and are explicitly encouraged (e.g. South America, Asia or Africa). The PhD process will be accompanied by
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academic staff and might be involved in teaching at under/postgraduate level as well as funding acquisition and (global) outreach, if desired. International networking and collaborations are regarded as an
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and analysed to advance the use of Creative AI? Applicants are encouraged to collaborate with relevant project partners from the public and/or private sectors within the MishMash network where
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the UK’s net-zero and clean energy ambitions. The role sits at the interface of materials science, chemical engineering, and hydrogen energy. The post involves hands-on experimental research, including
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processes and environmental engineering principles to ensure sustainability is embedded in the planning Experience modelling hydrological processes Experience of network simulation modelling i.e. for water
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series of international networks. Apply for this job Deadline 3rd May 2026 Employer University of Oslo Municipality Oslo Scope Fulltime (1 positions) Fulltime (%) Duration Project Place of service
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. Strong (inter-)national network in field of application. Experience with high-performance computing (HPC) and large datasets. Experience with machine learning applied to geophysical signals. Experience in
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within a vibrant international network of top interdisciplinary collaborators and partners on areas like youth well-being and mental health, inequalities and social stratification, population and
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Networks. Knowledge of and experience in Python, TensorFlow, Keras, or other Machine Learning toolboxes, is essential. Knowledge of and experience in Large Language Models is highly relevant. The successful
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workflows between field acquisition teams, data center staff, and research collaborators to ensure seamless data transfer and integration. -Support daily operations of servers, networks, storage, and cloud