Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
of acoustic wave propagation in moving fluid and physics-based machine learning (ML) methods. Support experimental design in the laboratory, carry out data processing and to use the experimental results
-
Interview Motivated in learning new methodologies and applying new knowledge Essential Interview Knowledge of the approximate Bayesian machine learning (e.g. MCMC) (assessed at: Application form/Interview
-
of industry-specific skills, and access to hotfire facilities at Westcott, Machrihanish, and elsewhere where you will build and hotfire your own engine. You can learn more about the programme at r2t2.org.uk
-
Machine Learning Approaches. You will have access to the excellent training opportunities at the University of Sheffield, and will spend time on site at Procter and Gamble. A range of highly desirable
-
development, machine learning and signal processing, and system integration. We are interested in working on different areas to improve the BCI technology. These areas include (but are not limited
-
and techniques. In addition, you will combine study and work-based learning to achieve the National Apprenticeship Standard - Laboratory Technician Level 3, which will span the full two years of your
-
round Details This project explores how machine learning and artificial intelligence can transform the scholarly digital editing process, not only by potentially automating and enhancing editorial
-
tested in controlled, structured synthetic environments. This approach generally leads to their spurious adoption in clinical practices. With the advances of machine learning (ML), AI and virtual reality
-
Application Deadline: Applications accepted all year round Details Self-driving laboratories (SDLs) combine the power of artificial intelligence (AI) and machine learning (ML), robotics, and automation
-
in the world and will develop skills in machine learning, observational and theoretical astrophysics. For more information on this project please contact s.littlefair@sheffield.ac.uk Information