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Offer Description MSCA Doctoral Network EMANAIRE, DC10: AI-Mediated Communication and Collaboration Norms at Work Position details Recruiting institution: Hanken School of Economics, Department
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Offer Description Doctoral Researcher: MSCA Doctoral Network DC 06: AI Co-Creation, Morality, and the Inner Good in Creative Industries Position details Recruiting institution: Hanken School of Economics
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Description New technologies in electrical distribution networks. • design of new components for medium-voltage distribution systems, with a focus on special transformers and power semiconductor technologies
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network discovery and individualized circuit targeting, multimodal concurrent brain stimulation-recording, and computational modeling. We bridge invasive approaches, including intracranial electrical
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project For an information package including full details of the post, selection criteria and application process see https://ore.ucc.ie/. The University, at its discretion, may undertake to make
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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 4 days ago
, with the possibility of additional one-year renewals. The position is funded by the SFB/TRR 247 collaborative research network “Heterogeneous Oxidation Catalysis in the Liquid Phase” and will be jointly
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specific requirements: a) Experience in the application of data analysis and machine learning methods to scientific data (e.g. multivariate analysis, chemometrics, neural networks, classification
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for this vacancy, this concerns a joint PhD position with KU Leuven as the main institution and primary workplace (and VUB as the partner institution).• Subject-matter expertise and an international research network
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applied research in the domains of food and biobased materials. Where to apply Website https://www.academictransfer.com/en/jobs/364061/machine-learningai-researcher-a… Requirements Specific Requirements You
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responsibilities will include: Identification of key microbial species in Antarctic coastal sediments using network analyses Investigation of the genetic repertoire of these key species to elucidate their eco