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Field
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vision systems, on the consideration of strong constraints on processing times and on the use of machine learning techniques in specific contexts (e.g. embedded targets, little data or explainable AI
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-driven energy systems research – scalable, transparent, and interoperable. Your tasks in detail: Development of a structured description format for the unambiguous and machine-readable characterization
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approaches that combine artificial intelligence, machine learning, natural language processing, and social sciences. This collaborative and cross-sectoral approach aims to produce robust methods for evaluating
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-flexible technologies, and integrate machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their
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at the Department of Computer and Information Science will focus on the usability and interaction with semantic technologies. Based on the semantic web technology stack for implementing DPPs, and an ontology-based
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investigate online feature engineering, continual learning and uncertainty quantification. Balance performance with governance. Projects will evaluate risk-adjusted returns alongside interpretability
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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at Aalto University (https://into.aalto.fi/display/endoctoralsci/How+to+apply#Howtoapply-Eli… ) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science
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, unsupervised and reinforcement learning that can be combined with, enhance or replace methods from computational engineering and computer simulation explore and evaluate usability of system architectures such as
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(or equivalent) in Computer Science, Artificial Intelligence, Engineering or a closely related field; Solid background in machine learning and/or evolutionary optimisation; strong programming skills (Python/C