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advertisement About the positions Interested in pursuing a PhD in machine learning in an interdisciplinary and collaborative environment in Norway? Integreat - Norwegian Centre for Knowledge-driven Machine
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applications for position as PhD Research Fellow in Adaptive AI Environments for Biofeedback and Motor Learning available at Department of Technology Systems (ITS), University of Oslo. Expected start date
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deadlines Language requirement: Good oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https
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dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently multi-agent, strategic, and resource-constrained. Each agent has its
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an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no . We fulfill our mission most effectively when we draw upon our
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Knowledge about relevant programming languages (Python, Perl, R) and biostatistics Ability to work in high-performance computing environment with workflow systems (Nextflow, Snakemake), Docker etc. Excellent
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multidisciplinary team working on systems that enable users to become immersed in remote physical environments, observe them, move in them, and physically act in them, and experience the effects of their actions
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and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and
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well as for maritime traffic surveillance. The project will benefit from the anomaly detection research environment in the Norwegian Center for Knowledge‑driven Machine Learning (Integreat ) and the ongoing project
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academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no . We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds