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Field
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vehicle (AV), allowing for automated detection, prediction, mapping, and planning. During the vehicle’s operation, data is obtained through a myriad of sensors in an AV—including RADAR, LIDAR, cameras, and
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resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge on control is highly preferred. Have experience and commitment to supervising student
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of oil spills in the ocean based on satellite imagery. A key focus will be to develop oil spill segmentation approach based on optical sensors, and how this can be integrated with SAR sensors, current
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large, highly diverse and multi-modal datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet
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Chemistry o Combinatorics, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory
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Engineering or related areas. Experience in research activities related to electrochemistry, biosensors, namely, construction of DNA-based sensors and paper-based electrodes. In case the Master degree
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practice of sensor development, battery manufacture and testing. You will ideally have experience of battery development including the experimental assessment / characterisation of battery and/or novel
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(OpelRT or Typhoon), electrical system design for better efficiency and system resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge
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Computational Condensed Matter Physics and Materials Sciences o Theoretical and Computational Biophysics o Soft Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal
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us to build/learn generative, probabilistic forward models of users and their physical and computational environments. This will involve modelling sensors, developing dynamic models for control and