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Field
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, and assisting research faculty and users with operation of the systems. Requires highly experienced individual skilled at managing Linux-based supercomputing clusters, scalable parallel file systems
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Gaussian processes with learning capabilities is essential, including data association and other Bayesian methods. You will join a collaborative research environment at the University of Sheffield, working
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spectroscopy Spatial light modulation Laser locking, optical resonators Optical interferometers Gaussian beam profiling CAD development Soldering PCB development FPGA development Digital signal processing (DSP
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topology of Gaussian random fields, and random Laplace eigenfunctions. Analysing some features of random cusp forms. Developing probabilistic framework to explain spectral phenomena. Conducting numerical
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related to staff position within a Research Infrastructure? No Offer Description · Literature search for materials or processes of interest for energy applications (e.g. photovoltaics, HER, ORR and CO₂RR
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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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in the area of probabilistic methods in machine learning. These include applications of Random Matrix theory and Gaussian processes to Deep Neural Nets. Teaching may be required. Education and
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simulation, Bayesian methods, Gaussian Process regression algorithms with uncertainty quantification of the impact of environmental conditions and other factors on the developed solutions, perform physical
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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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. 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