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Field
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novel photonic techniques such as time resolved single photon technologies, spectral imaging, and optical fibre sensors to tackle clinical/biomedical challenges and other real world applications. Our work
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construction machinery to improve efficiency, adaptability, and safety under varying operating conditions. The work will involve designing and prototyping intelligent control algorithms, developing runtime
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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states within the brain. Research Focus Areas: Our laboratory has three main research thrusts: 1. Engineered Cellular Sensors for Neurodegenerative Disease Detection and Treatment - Developing receptors
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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/field personnel in research. Initial studies will focus on burn wounds, improving healing and assessing multiple wound factors using imaging and sensors. What you need to know Salary: Compensation will be
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advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You will work closely with colleagues both
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and nanostructuring, all guided by advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You
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) technologies (e.g. Geospatial Analysis, Geocomputation, Spatial Modelling, Robotics, Sensor Technologies, ML etc.) to carry-out rapid, wide-area mapping, 2.5D real-world modelling and highly automated feature
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods