28 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at University of Surrey in United Kingdom
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/structural/mechanical engineering with experience and interest in structural dynamics, vibrational analysis, train-track-bridge interaction, signal processing, data science and machine learning. The successful
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techniques to students and staff, helping others learn and succeed • Monitor and support Health and Safety practices, including risk assessments and lab upkeep • Assist with demonstrations at Open Days, Taster
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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
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language processing for accessible science to contribute to the Terminology-Aware Machine Translation for Accessible Science (TaMTAS) project. The project is funded by EPSRC under the CHIST-ERA Call 2025: Science in
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which we provide will teach you everything you need to know to succeed, but there are a few requirements you’ll need to start: Basic computer literacy. Previous experience of working in a kitchen or pub
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. To acquire and maintain an excellent working knowledge of the student records system (SITS) and timetabling system (CMIS) to work effectively and efficiently and to contribute to process improvements
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(early evenings and weekends) but shift patterns are provided well in advance. You should be confident in your use of Microsoft packages such as Outlook, Word, Excel and Teams with the ability to learn
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evidence of their capability to teach marketing analytics and related areas across the curricula of UG and PG programmes. Industry experience, particularly in marketing-oriented roles with either MNCs
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range of disabilities, including autism, ADHD, mental health conditions, and Specific Learning Differences. This is an exciting opportunity to be part of an inclusive, friendly and progressive team
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-acoustic waves are weak, noisy and broadband. To address these challenges, this project will employ deep-learning techniques for signal denoising and 3D dose reconstruction. The project is in close