96 data-"https:"-"https:"-"https:"-"https:"-"AALTO-UNIVERSITY" positions at Aalborg University in Denmark
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, computationally efficient gas radiation models suitable for CFD implementation Perform accurate CFD simulations of green fuel combustion in a CVCC and validate the CFD by detailed experimental data to be provided
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experiments, integrating experimental data collected during loaded magnetic resonance imaging scans of the human knee joint with the ex vivo findings. By working with in vivo models, you will contribute
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at www.es.aau.dk. Your work tasks This PhD project is part of a bigger Novo Nordisk Foundation (NNF) New Exploratory Research and Discovery grant entitled: Information Theoretic Disentanglement of the Exceptional
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to contact us. For professional information, please contact Associate Professor Florin Iov, fi@energy.aau.dk , +459940 9266 . Further information Read more about our recruitment process here The appointment
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with leading Danish and European companies, as well as international academic partners. The AI4OR group addresses complex, high-impact problems requiring advanced modelling, data analysis, and
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are in part funded by a DFF: Sapere Aude project (“Building TRUST in Text: Linguistically Motivated Language Model Detection”) and an NNF: Ascending Data Science Investigator project (“LM2-SEC
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professional information from Associate Professor Kristian Olesen, Research Group of Planning for Urban Sustainability, 99407211, kristian@plan.aau.dk. Qualification requirements Appointment as assistant
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, such as motion capture, electromyography, inertial measurement units, advanced data processing, numerical methods, optimization procedures, statistics, research ethics and management of personal data
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nexus supported by data-driven methods. This is a full-time position, expected to start on 1st of February 2026 or as soon as possible thereafter. This position is a six-year position as an assistant
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to the project, uniting experts in battery technology and acoustic signal processing and machine learning. The goal is to harness advanced data science techniques to establish a novel paradigm for online non