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motivated candidate with a strong background in statistics and/or machine learning. Areas of particular interest include, but are not limited to: Causal Discovery and Causal Inference Extreme Value Theory
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provide the possibility for the student to work with LLMs and machine learning. Your competencies Interest in learner centered technology design, in particular how AI systems can scaffold reflection, agency
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(DInSAR). Minute surface uplift and subsidence signals will be automatically detected using machine-learning workflows, enabling systematic, user-independent identification of drainage events every 6–12
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Control of Buildings (https://annex96.iea-ebc.org ). Responsibilities and qualifications The primary objective is to advance scalable modeling methodologies for building energy systems by combining physical
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leading Human-Computer Interaction venues. Your competencies You hold a master’s degree in human-computer interaction, computer science, interaction design, applied artificial intelligence, architectural
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Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing Assistance in Complex Acoustic
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Computer Science, Electrical/Electronics Engineering, Data Science, Cyber-Physical Systems, or a closely related discipline. Machine Learning & Data Processing: You have solid experience developing and applying
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related to human-computer interaction and software engineering. Your competencies Applicants should have a strong interest in human-robot interaction and the role of emerging technologies in healthcare
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the Marie Skłodowska-Curie Actions (MSCA) grant on WindConnect project. The project The WindConnect (wind farm control and integration in sector-coupled power systems https://cordis.europa.eu/project/id
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-coupled power systems https://cordis.europa.eu/project/id/101227683 ) consortium unites leading experts from academia and industry across Europe, leveraging expertise in wind energy, power systems, power