Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
-
developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
-
Programme: Hybrid CFD and process simulation for process intensification of post-combustion CO2 capture School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof
-
day/week) to support aspects of a process evaluation work package for a multicentre randomised controlled trial of AI-assisted ultrasound technology in obstetric screening. Supported by an experienced
-
-care For informal enquiries about this job contact Stephen Bradley, Senior Lecturer: on stephen.bradley @sheffield.ac.uk Next steps in the recruitment process It is anticipated that the selection process
-
inequalities shape carers’ lives using qualitative and creative methods (e.g. Theatre of the Oppressed, or others). 2) To support the co-production process across our team and partner organisations (e.g. Black
-
protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
-
international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
-
discovery process, leading to more economic and effective drugs that can significantly improve the health and lifestyle of millions. The resulting methods are also expected to have an impact in materials
-
discovery process, leading to more economic and effective drugs that can significantly improve the health and lifestyle of millions. The resulting methods are also expected to have an impact in materials