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This PhD project, part of the REACT MSCA Doctoral Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing
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and fluctuating electricity prices, the main objective will be to develop a control-oriented model and algorithm to alter the lighting, CO2 dosing, and air circulation that satisfy the crops' needs
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-static beamforming methods, and semi-tomographic reconstruction algorithms that enable high-quality 3D visualization of the abdominal aorta. In addition, you will develop algorithms for segmentation
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notions of resilience have to be developed along with algorithms to check resilience of machine learning models. Research is conducted in the fields of automated reasoning, probabilistic verification, and
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sovereignty, and cyber-electromagnetic resilience. The PhD researcher will primarily work within Tilburg University’s AI research infrastructure, focusing on algorithm development, model training, and
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) for algorithm development, control design, and data analysis. Confidence and interest in testing and iterating technology together with patients, in the lab and in the clinic. Excellent organizational and
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wearable-sensor (IMU) data and human motion analysis. Solid programming skills (ideally, in Python) for algorithm development, control design, and data analysis. Confidence and interest in testing and
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developing and benchmarking planning algorithms, and as a system-level validation tool before real-world deployment. By the end of the contract, the postdoctoral researcher is expected to play a leading role
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missions intelligently and safely without revealing sensitive information? As a PhD candidate, you will develop verifiable, secure-by-construction planning and control algorithms, contributing to trustworthy
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sensitivity analyses across pathology severity, body morphology, camera viewpoint, and environmental conditions Develop a single-camera, home-based markerless system Test the algorithm across lab and home