Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
test the extent to which these generalise across brain areas and species. You will be working with an interdisciplinary team led by Prof Andrew Jackson funded by the Advanced Research and Invention
-
" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic
-
VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
-
VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
-
the supervision of Prof. Muhammad Ali Imran and Prof Jonathan Cooper, who will act as Line Managers. The project particularly emphasizes ambient and remote sensing techniques, connectivity for healthcare, and
-
Predictive Control (MPC) algorithms, innovative coalition-formation techniques, and validate these through high-fidelity simulations. You will design, implement and validate innovative data-driven economic
-
, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
-
career, whether in industry or academia. Please contact Prof. Isaac Chang (Isaac.Chang@brunel.ac.uk ) for an informal discussion about the project. Eligibility Applicants will have or be expected
-
Research Studentship in Numerical Optimisation and Control 3.5-year D.Phil. studentship Project: Embedded Optimisation for Autonomous Spacecraft Control Supervisors: Prof Paul Goulart The project
-
abort (or not engage) if the bright white lines that fit a defined and rigid expectation are not clearly visible. These systems use algorithms, rather than AI machine learning, to detect road markings and