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Field
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sensors (e.g., electrochemical, metal-oxide, optical) with different gas mixtures; Establish calibration strategies to the different sensors; Develop a method to collect gas mixtures from the gas sensor
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system ROS/ROS2, PX4, LiDAR, Stereo and Monocular vision, Perception, AI, ML, Path Planning Control, Sensor Fusion Algorithms;; - Previous experience in Deep Learning with LiDAR and vision systems
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. We are seeking a highly motivated Laboratory Technician to join our team under the ATE Agenda funded by the PRR framework. We expect the candidate to contribute to electrochemical sensor data
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Engineering, specialization in Autonomous Systems. Requirement 3: have proven academic experience in implementing hardware and algorithms in Python and ROS, and in developing ground robots controlled by
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mobile applications in the health field (e-health & m-health). Development and integration of algorithms from the research group. Testing and validating technologies in real scenarios, collecting user
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randomness and energy efficiency. However, these arrays suffer from mismatch differences between nominally equal neurons due to the fabrication process. The mismatch differences will be compensated by using a
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Agenda funded by the PRR framework. The candidate will contribute to the development of protocols for bioanalyte concentration and detection using optical sensors, microfluidic devices, and magnetic-based
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sensor for the early detection of pathogenic bacterial species. As part of this development, we are pioneering a novel approach for Volatile Organic Compound pre-concentration. We are looking for a two
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will be the following: Conduct original research in the design and development of mixed-signal and analog ICs, including data converters (ADCs/DACs), PLLs, amplifiers, power management and sensor
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on dissecting the role of the Aryl Hydrocarbon Receptor (AHR) as a dynamic and key sensor of the microenvironment and homeostasis (focus on host-microbe interactions and cancer), capable of fine-tuning different