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Multi-Sensor Data Fusion and Smart Decision Making School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova Application Deadline: Applications
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will collaborate at the development of innovative methodologies for the detection and tracking of objects with radar and optical sensors. The techniques will be applied to the protection of aircraft in
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workflows for engineering design and optimization of fusion reactors and facilities needed on the path to a Fusion Pilot Plant (FPP). The Principal Research Scientist (Managing) will also deploy and use those
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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, thermal, depth, LiDAR, acoustic, sonar and radar sensor data, with established research lines in 3D reconstruction, and Edge AI for resource-constrained deployments. Where to apply Website https
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an autonomousmanner, only within the limits of the research program available on the web address (Number 290) https://www.uniud.it/it/albo-ufficiale Research assignment financed by INTERREG IT-HR 2021-2027 BRIGANTINE
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YOUNG RESEARCHER IN THE FIELD OF EARLY DETECTION OF THE HEALTH STATUS OF PLANTS USING REMOTE SENSING
participate in the development of methods for the early detection of biotic and abiotic plant stress using remote sensing data acquired with unmanned aerial vehicles and multi-sensor systems. The tasks will
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collaboratively with cross-functional teams. You are a responsible, communicative and flexible person. Your English is fluent, both spoken and written . Bonus points: Expertise with sensor fusion approaches and
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strong expertise in field robotics. Specific application areas of focus are robotics for mines, aerial inspection of aging infrastructure, multi-robotic search and rescue, multi sensorial fusion and
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Lyudmila Mihaylova Application Deadline: Applications accepted all year round Details This PhD research is focused on multi-sensor data fusion for decision making. The project aims at dealing with large