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the mentorship of Dr. Peyman Benharash, the candidate will contribute to ongoing research into the design and performance of non-invasive physiologic sensors to aid patient recovery and improve surgical outcomes
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and the automation of commercial vehicles and unmanned aerial platforms, focusing on environment-perception techniques (e.g., multi-spectral cameras, laser- and radar-based sensors, odometry, and
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decisive importance for lifetime performance modelling. The key challenges are the robust integration of a sensor system in the structure and the analysis of measured signals, which are typically strongly
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that support innovative biomedical and behavioral research in naturalistic settings. This position is responsible for building and deploying sensor-based data collection platforms, developing software for data
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or reinforcement learning o Sensor fusion and state estimation o Motion planning and control • Excellent programming skills in Python and/or C++. • Experience with ROS
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potential for covering the growing need for high-precision sensors, both for basic science and for industrial applications. State-of-the-art quantum sensing methods rely on spin defects hosted in three
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. The objective is to develop and validate miniature fibre-optic sensors capable of measuring pressure and temperature in a new generation of ultra-high-pressure rheometers. The intended application is a slit-die
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networks are typically developed for a specific radar configuration and task, and often generalize poorly to other sensors. At the same time, large scale radar datasets with high quality labels remain scarce
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. Responsibilities Integrate and evaluate the STLINK-V3PWR power measurement platform. Collect, synchronize, and analyze sensor, runtime, and power consumption data. Extend the digital twin to model both sensor
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Internet of Things sensors that will continuously monitor critical parameters such as temperature, humidity and food quality in real time. The data captured through the deployment of these technologies will