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explore relations between energy and non-classicality, both to provide new ways to characterize non-classical quantum states of light, and optimize processes to produce them. Context and goal of the project
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underwater vehicles. We will explore advanced non-parametric mapping techniques based on our prior work in the area of Gaussian Process based Simultaneous Localisation and Mapping (SLAM) and recent advances
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area of Gaussian Process based Simultaneous Localisation and Mapping (SLAM) and recent advances in non-parametric, 3D environment modelling. We will assess the utility of these tools for map-building
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. Certificates/Credentials/Licenses Computer Skills Academic and research software relevant to job duties (Linux operating system, Gaussian/ORCA, AMBER/OpenMM, coding skills in Python). Supervisory
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new theory, models and algorithms in the areas of computer aided design, geometric modeling, deep learning, LLMs, etc. Develop and implement algorithms and prototype tools for 3D content generation
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. For admission and curricular evaluation purposes, proven skills in programming, preferably Python and/or C++; computer vision; computer graphics; real-time 3D rendering; 3D Gaussian Splatting, Mip-Splatting, LOD
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on Artificial Neural Networks and Gaussian Process modelling, to accelerate processing optimisation. Consolidate experimental, techno‑economic, and sustainability data into robust technical evidence packages
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, recovery and separation of supernatant, and drying process. Support AI‑enabled data analysis, including collaboration on Artificial Neural Networks and Gaussian Process modelling, to accelerate processing
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) Theoretical Modeling: Develop and refine models for entanglement harvesting using continuous-variable quantum information theory and Gaussian quantum states steering. (2) Experimental Simulation: Simulate