-
focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
-
paleoenvironmental reconstruction reef geology and ecosystem response The overarching project design reflects the highly interconnected nature of the three aims, with the PDRA contributing across all themes
-
: geochronology, sea-level reconstruction and ice-sheet dynamics geochemistry, paleoclimate and paleoenvironmental reconstruction reef geology and ecosystem response The overarching project design reflects
-
-based algorithms (e.g., GNNs, deep reinforcement learning) design and simulate dynamic models of megaproject systems prepare and submit journal articles to high-impact publications contribute
-
learning at scale. Research directions include designing algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating
-
, thermochronology, tectonics, geodynamics, surface processes, relational database design, and geological data science. experience using GPlates, Underworld, Badlands, goSPL, Pecube, GLIDE, Age2Exhumation, and/or
-
disciplines including aerospace, combustion, design, fluid mechanics, materials, mechanical, mechatronic and robotics engineering. To learn more about the School click here . The Clean Combustion Group