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Field
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- HydroGraph ) Start date: 6th October 2025 Project Description – The aim is to develop a fundamental understanding of the reinforcement mechanisms enabled by FGA-1, including its impact on application
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highly motivated and independent candidate with strong analytical skills. The candidate should have a strong desire to develop novel computational methods and ML/AI tools to address challenging problems
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statistical analyses to assess stability and plasticity of multisensory representations Collaborate with experimental partners and team members to interpret findings and develop brain-machine interface
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nonlinear control and optimisation to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation
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respond over time (e.g. changing shape), controlled by the arrangement of differential materials within them. The goal of this project will be to develop responsive 4D-printed biomaterial devices for drug
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printed parts and we are still developing new leading-edge materials to grant them new capabilities. Advantages: In this PhD studentship, you will develop the materials, methods, and designs necessary to 3D
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of differential materials within them. The goal of this project will be to develop responsive 4D-printed biomaterial devices for drug delivery or regenerative medicine. The student will formulate new 3D-printable
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mechanisms, with the current generation having significant drawbacks, including low energy efficiency, high operating voltage or temperature. This project will develop the materials, methods, and designs
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it is possible to tune the FTU by changing the nozzle size, it may not be practical or economically feasible to expect manufacturers to develop nozzles of various sizes to enable facile dosing
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mechanical fatigue—individually and sequentially, followed by electrical breakdown testing to assess their impact on the dielectric performance of the material subsystems. The target is to develop a