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to join our team. Our lab focuses on developing and applying innovative statistical machine learning methods, single-cell multi-omics, and systems immunology approaches to investigate immune-mediated
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for green hydrogen continues to rise, the high energy demands associated with conventional methods like electrolysis highlight the need for alternative approaches. Photocatalysis, leveraging solar energy for
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from estimation and optimization theory to hardware design. The specific topic of the project falls in the intersection of statistical signal processing and applied mathematics and is in particular
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. Exploring how these models can enhance human-computer interaction and improve our understanding of multimodal communication.To do so, you will have full access to motion-capture and virtual-reality labs, 3D
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19 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Programming Engineering » Computer engineering Engineering » Electrical
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no more than three years prior to the application deadline*. A working knowledge of advanced methods in High-Energy physics, in particular quantum field theory and particle physics is required. Familiarity with
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both theoretical challenges and practical applications. Key Responsibilities: Develop innovative methods and tools for adaptive, AI-driven embedded algorithms to support real-time analytics and decision
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physics and urban meteorology groups at INAR. The computational aerosol physics group uses computational and theoretical methods to understand cluster and particle formation for atmospherically relevant
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contact both, and Your profile PhD in Information Systems, Computer/Data Science, Software Engineering, Applied Mathematics, or a related field Experience in publishing high-quality research, as
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observational data, and compare the results with those from other emulators of similar datasets (e.g. Gaussian Process methods by the project lead). These results will inform the IPCC AR7, and adaptation and