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sensor networks are required. To be considered, all applicants must submit a cover letter, curriculum vitae, transcript of degree/ copy of highest degree, and a research statement, all in PDF format
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Description of the workplace The Division of Secure and Networked Systems
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universities, with access to unique deposition and test facilities and strong international collaboration networks. This position provides the opportunity to contribute directly to the energy transition and to
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-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and results
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predictive maintenance in chemical plants. Key Responsibilities: Create and implement hybrid AI models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks
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to a future in which we can rely on better robots, autonomous networks, and other smart systems – impacting domains such as healthcare, transportation, and other areas of our society. These systems
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Trustworthy Graph Machine Learning for Population Scale Networks Job description We invite applications for a postdoctoral researcher to work on fundamental techniques for trustworthy graph machine
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an inspiring research setting at one of Europe’s leading technical universities, with access to unique deposition and test facilities and strong international collaboration networks. This position provides
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the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting
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rate, and wearable sensor data. Develop and validate comfort prediction models targeting high prediction accuracy using a dynamic driving simulator and real-world operating conditions. Integrate thermal