39 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions at UNIVERSITY OF SURREY
Sort by
Refine Your Search
-
queries, book retrieval and help manage our learning spaces, ensuring a positive and inclusive library experience for everyone. About you We are looking for an enthusiastic and confident individual with a
-
strong international track record in content provenance and authenticity research spanning computer vision, watermarking, machine learning, privacy-preserving technologies and open standards. We have
-
machine-learning, predictive-modelling or multivariate methods to behavioural and/or EEG data. Proficiency in R, MATLAB and Python. What we can offer In return we offer a generous pension, relocation
-
workshop facilities and provide expert technical support to engineering and research activities across the University. No two days are the same. One day you could be machining a complex component from a CAD
-
the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use similar techniques to make a statistical inference of the population of subhaloes by
-
such as Application Gateways (WAF), Firewall, App Service Plans, Azure Virtual Desktop and Virtual machines. This would include refining requirements, applying a firm technical understanding to develop
-
dedicated team is essential. Applicants must be highly computer literate with a strong grounding in Microsoft Word, Excel, and Outlook. Experience of working with Sage 50 Accounts or similar in a previous
-
relevant defective information and repairs. All defects to be reported immediately to the help desk for further action. Must be computer literate and work well with computer/tablet systems What’s in it for
-
a cover letter outlining how you meet the requirements of the role. If you’d like to learn more about the role, please contact Imane Strudwick (Technical Manager) via [email protected]
-
, physiology and general medicine, and specialities. The first year of the course is structured in themes, based around clinical cases, which enables medical students to learn clinically relevant biomedical