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embedded FPGA-based intelligence near seismic sensor arrays, you will explore methods to maximize prediction performance while minimizing data transmission and latency. Your key tasks include: Evaluating
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Marie Sklodowska-Curie Actions Doctoral Network BlueOcean This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large
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(e.g., doer–checker architectures), explaining recommendations to operators, and remaining robust to sensor faults, distribution shifts and previously unseen operating conditions. Applications will
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prescriptive maintenance system for Genie’s lifting equipment. The project focuses on connected, partially connected, and non-connected machines, transforming telematics, onboard sensor data, and historical
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Horizon Europe Marie Skłodowska‑Curie Actions (MSCA) Doctoral Network ‘ENDURE’ on Enabling Scaled Production of Durable Natural Fibre Components coordinated by the Technical University of Denmark. See
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Marie Sklodowska-Curie Actions Doctoral Network BlueOcean Employer UNIVERSITY OF SOUTHAMPTON Location Southampton, United Kingdom Salary £43,994 to £47,279 Per annum, subject to bi-annual review due
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comparable to sensor noise? How can full-field uncertainty be modelled and propagated to support large-scale change analysis? Approach: You will combine advanced robotic localisation and high-resolution
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-based plant research Interest in linking physiological processes with imaging and sensor-derived plant traits Experience in quantitative data analysis and statistics Experience with R, Python or
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collaboration with leading academic and industrial partners, access to state-of-the-art robot platforms, full-scale industrial sites, multi-sensor labs, and advanced network testbeds. The teams are
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partners, access to state-of-the-art robot platforms, full-scale industrial sites, multi-sensor labs, and advanced network testbeds. The teams are highly international, and the working language is