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Field
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: Autonomous Systems and robotic platforms Agricultural Robotics and precision agriculture technologies Artificial Intelligence and Machine Learning applications Computer Vision and sensor integration
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to monitor oceanic CO2 uptake with improved confidence. Any future observational network utilises a range of instrument/sensor technologies, deployed on different platforms, and measuring multiple variables
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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
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. The second pertains to a NASA-funded project to design and fly an airborne water vapor Lidar sensor at supersonic speeds. In either role, the successful applicant will apply optical analysis techniques (theory
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robotics, localization, mapping, and multi-modal sensor fusion; (b) proficiency in programming languages such as Python and C++; (c) demonstrated ability to conduct independent research and contribute
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borehole seismic data obtained with various sensors. Assist in planning, design and implementation of field experiments to collect high quality geophysical data for research projects utilising fibre optic
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prepared based on the findings with a focus on facilitating the replication at city and national levels. Each bike will be instrumented with GPS sensors to understand preferred cycling routes. The data will
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to twelve months] Duties The appointees will assist the project leader in the research project - “Ultrasensitive optical microcavity sensor-integrated optofluidic biochips for early disease diagnosis
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-bioreactor systems for organ-on-a-chip applications. Integrate sensors, microfluidic control, and environmental regulation into compact bioreactor units. Collaborate with biologists and engineers to validate
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towards this goal. The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://www.hvl.no/en/research/phd