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the advent of the Internet of Things (IoT), any sensor can be interfaced with a local network or the Internet. This massive deployment has created many security issues and associated solutions
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] Subject Areas: Physics / Hard Condensed Matter Theory , Machine Learning , Material Science , Physics , Quantum Information Science , Soft Condensed Matter Theory , theoretical condensed matter physics
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Python and experience with deep learning frameworks (e.g., PyTorch) Experience in working with time-series data Good understanding of Internet of Things, wireless communication network and systems Strong
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that the developed methodology achieves enhanced reliability, robustness, and feasibility, aligning with the targeted entry into service by 2035. This position is embedded in the Intelligent Systems Prognostics (iSP
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with the targeted entry into service by 2035. This position is embedded in the Intelligent Systems Prognostics (iSP) Group within the Faculty of Aerospace Engineering at Delft University of Technology
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office allowance of €2 per day. Reimbursement for sustainable commuting: walking, cycling, and public transport. A monthly internet allowance of €25. An options model in which you exchange benefits
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flocculation dynamics. ● Test and refine low-cost optical sensors, including a blue-light absorbance sensor for dissolved organic matter. ● Integrate sensor outputs into process control systems (stepper motor
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for dissolved organic matter. ● Integrate sensor outputs into process control systems (stepper motor–driven coagulant dosing). Desired qualifications: ● PhD in Environmental Engineering, Electrical/Computer
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, such as interoperability and security between elements inside the smart factories composed by Cyber-Physical Production Systems (CPPS) in the Industry 4.0 and the Industrial Internet of Things (IIoT), in
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availability of data and connectivity through the Internet of Things create new opportunities to incorporate real-time insights into decision-making, combining tractable modelling with provably efficient