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Field
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PhD position on Closed-loop testing for faster and better EM evaluation of complex high-tech systems
with antennas, evaluate different algorithms for EM field strength data, investigating the minimal needed sensors (up to nine), and controlling the equipment using in-line measured data (closed-loop
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. The research includes artificial intelligence and autonomous systems that operate in collaboration with humans and adapt to their environment using sensors, information, and knowledge, creating intelligent
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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of such use cases and applications compiling algorithms for use on early-generation hardware. We also encourage applicants interested in other quantum technologies such as quantum sensors and simulators, and
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. Familiar with robotic control systems, perception, and kinematics. Comfortable working in Linux environments with tools such as Git. Knowledge of MATLAB for simulations and algorithm prototyping. Basic
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research trends Develop new algorithms, either directly or via programs of research to be conducted by our APPN nodes Create and maintain a list of approved trait algorithms that are agreed by all APPN Nodes
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-time control & optimization algorithms. Pilot demonstrations on partner radio telescope facilities such as APEX and the Sardinia Radio Telescope may be possible, depending on the interest of the PhD
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developing novel real-time control & optimization algorithms. Pilot demonstrations on partner radio telescope facilities such as APEX and the Sardinia Radio Telescope may be possible, depending on the interest
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collaboration between the OU and Teledyne e2v (T-e2v), a world-leading manufacturer of scientific and industrial image sensors. The CEI is dedicated to conducting research into advanced imaging technologies
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with MoniRail Ltd and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected