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PhD Stipend in machine learning methods for the analysis of IoT time-series data. At the Technical Faculty of IT and Design, Department of Computer Science, one PhD stipend in machine learning
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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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(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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Professorhip grant, which you can learn more about here: https://www.cnap.hst.aau.dk/lundbeck-professorship As a PhD fellow your tasks include: Conduct research under the supervision of senior CNAP staff members
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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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that aims to redesign how students learn programming through AI-driven, dialogue based, and pedagogically grounded tools. The PhD candidate will contribute to a cross-faculty collaboration spanning the TECH
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD position on Understanding and
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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physics, HVAC systems, and thermodynamics. Control Expertise: Experience with advanced control strategies and/or machine learning techniques. Digital Engineering Skills: Familiarity with Building