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Field
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and sensor data processing, bioinformatics, systems biology, or biophysics. Familiarity with simulation environments, numerical methods, or machine learning approaches is an advantage. Fluent command
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that do not confer an academic degree, in the area or area related to that requested in the tender. Preferential factors: Have demonstrable experience in the use of machine learning algorithms applied
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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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intelligence, and research software engineering, and is interested in developing robust, transparent, and sustainable computational tools. Experience with first-principles electronic structure methods, machine
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, machine learning tools, and simulation techniques. If you thrive at the intersection of engineering, data, and advanced computational science, this position will allow you to contribute meaningfully
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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% of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique
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urban design with microclimate simulations and measurements, GIS and Digital Twin technologies, and machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based
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selection criteria Experience with machine learning or other relevant AI technologies Experience with condition monitoring, preferably within maritime domains Knowledge of ship machinery and systems Good oral