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, integrates, and evaluates innovative solutions in autonomous systems, including artificial intelligence (AI), machine learning, robotics, control systems, sensing technologies, and related disciplines
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
, scientific curiosity, and commitment to scientific excellence. Hands on experience with optics, fiber optics, sensors, miniaturized systems design and development. Programming skills in C++ and MATLAB
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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: Steinberg Centre for Simulation and Interactive Learning (SCSIL) The Surgical Performance Enhancement and Robotics (SuPER) Centre in collaboration with Steinberg Centre for Simulation and Interactive
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to understand how design and planning decisions affect health and wellbeing. Key Responsibilities are to design and test a measurement protocol combining wearable sensors, environmental data, and imagery-based
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analyze electrochemical oxidation/reduction studies to validate drug-dependent or biomarker-dependent electron transfer and sensor response. • Synthesize and characterize nanoparticles of various
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historical process data, sensor data, and laboratory findings) using advanced AI approaches such as unsupervised learning, transfer learning, and anomaly detection. Collaborate with process engineers and
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demonstrating technical familiarity with: Embedded system design for multiple sensors (flow, pressure, temperature) and control For consideration, applicants need to submit a cover letter, curriculum vitae with
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sensors, RGB/IR cameras, video systems, insect traps, and other devices to build predictive, AI- and machine-learning based models for monitoring grain quality and detecting deterioration due to mold
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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