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Field
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deployment, monitoring, and optimization of complex scientific data streaming workflows for current and future production infrastructures. The project will involve close collaboration with a team of systems
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at the Department of Philosophy, Classics, History of Art and Ideas (IFIKK), Faculty of Humanities, University of Oslo. Interdisciplinary knowledge and education are essential for addressing complex problems and
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evaluate distribution networks in OpenDSS; investigate feeder- and system-level impacts of DERs (e.g., load flow, hosting capacity, voltage regulation). Develop and refine T&D co-simulation platforms (e.g
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effectively in a collaborative, team-based environment A passion for tackling complex challenges to contribute to a more sustainable future Personal characteristics To complete a doctoral degree (PhD), it is
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Your job Are you passionate about cancer research? Excited to dive into biological pathways and complex data analyses in an epidemiological setting? Eager to work within an ambitious and
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Center and a member of the National Comprehensive Cancer Network (NCCN). We are among the top-ranked national programs in research and patient care with members holding $120M in annual direct research
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disciplines related to the UKRI-funded Supergen Network Plus on AI for Renewable Energy (SuperAIRE). You will also collaborate with different regional and national policymakers and stakeholders, including
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with a wide network of stakeholders, and explore new avenues for medical applications. For ongoing work and publications on this project, please see our website: www.cnnp-lab.com . This is a 12-months
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workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement
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of Denmark. The position is part of a larger EU project entitled “FEDORA - Federation of network optimisation services, simulation foresights, and data alchemy for adaptable, agile, secure, and resilient