270 computer-security "https:" "https:" "https:" "https:" "U.S" positions at University of Nottingham
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Recruitment video at https://mediaspace.nottingham.ac.uk/media/t/1_jdj4s55c To understand our recruitment process (including some handy tips and advice), please follow this link Understanding our application
-
the role profile. Refer to our candidate guidance on writing an application and the use of AI: https://www.nottingham.ac.uk/jobs/candidate-guidance/writing-your-application.aspx Hours of work are full-time
-
extended by mutual agreement. Applicants are invited to submit their applications via the application link https://jobs.nottingham.edu.cn/job/184369/ by 23:59 Beijing Time, 23 February 2026, which should
-
, safety, and cost. One of the most common causes of development delays is the presence of technical silos between specialised teams. Because the disciplines are tightly interconnected, a small change can
-
. We provide a structure for people to thrive, feel supported, valued and that their health, safety and wellbeing is being managed (including mental wellbeing). The aim and purpose of the School
-
funded project aiming to characterise rhythmicity in human skeletal muscle metabolism and how exercise affects it. The post holder will be responsible for the day-to-day running of this programme of work
-
awareness, and decision quality. The project will examine how system design, automation characteristics, and regulatory or governance constraints shape human performance and patient outcomes in safety
-
holders will be able to spend some time working from home if desired: Role 1 – Computer Science (UoA11) and Mathematical Sciences (UoA10) (primarily based at University Park and Jubilee campuses) Role 2
-
prospects for future project involvement should further funding be secured. This post is a full time (36.25 hours weekly) Fixed-term post for 6 months. About the team You will join the Nottingham Centre
-
, robust, and trustworthy when deployed in real-world, safety-critical environments. Together, we will advance the foundations of intelligent autonomous systems by combining modern reinforcement learning