675 computer-programmer-"https:"-"Inserm" "https:" "https:" "https:" "https:" "https:" "U.S" uni jobs at University of Sheffield
Sort by
Refine Your Search
-
Listed
-
Field
-
that the selection process will take place in the weeks following the closing date. We plan to let candidates know if they have progressed to the selection stage within two weeks of the advertised closing date. If you
-
consistency and quality of front-line services and process for all EDS activities, line managing the Receptionist, overseeing rotas and managing ad hoc cover arrangements. Independently plan and prioritise work
-
● Build the commercial proposition of the Spatial Living Biobank via development of the business plan and financial/cashflow needs. ● Test and retest value propositions through extensive and ongoing
-
communication and photonic quantum computing. These technologies are no longer theoretical; they are rapidly becoming reality thanks to industrial involvement. Examples include Quandela that has delivered
-
Advancing Human Motion Understanding through 3D Modelling and Foundation Models (S3.5-COM-ZChen) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr Zhixiang
-
implications Essential Application & interview Ability to assess and organise resources, plan and progress work activities Essential Application & interview Ability to work to a high degree of accuracy and
-
consist ofinterview questions only.. We plan to let candidates know if they have progressed to the selection stage on the week commencing 3rd February 2026. If you need any support, equipment or adjustments
-
Neuro-Symbolic AI for Trustworthy Clinical Decision-Making: Bridging Linguistic Fluency and Logical Reasoning in Large Language Models (S3.5-COM- Valentino) School of Computer Science PhD Research
-
engineers to monitor and maintain shell structures in real time. By combining data from sensors with advanced computer models, a digital twin can continuously track how a shell responds to changing loads and
-
Reinforcement Learning from Human and AI Feedback (S3.5-COM-Peng)