136 machine-learning-"https:"-"https:"-"https:"-"https:"-"U.S"-"U.S" positions at Cardiff University
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
- Learning Technologist The Cardiff Learning and Teaching Academy is offering an exciting opportunity to join its Digital Education Team. As part of a team of Digital Learning Professionals and Learning
-
, with various start dates. If you have difficulty accessing a computer, please call 029 2087 6137. Benefits We offer a leading and rewarding staff benefits package: 32 days holiday per year plus 8 bank
-
play a leading role in the analysis of large and complex genetic and electronic health records datasets with a range of Statistical and Machine Learning approaches, whilst leading a broad range of
-
technology (post-editing machine translation and the University translation memory output) and software to ensure accuracy, consistency, and value for money in relation to translations. Instruct and guide
-
. Willingness to learn complex statistical analyses of fMRI data (this might include analysis methods such as multivariate data analysis, machine learning or computational modelling) Desirable CriteriaExperience
-
play a leading role in the analysis of large and complex genetic and electronic health records datasets with a range of Bioinformatics tools, Statistical and Machine Learning approaches, whilst leading a
-
computer and IT skills, Kinetics, Oracle, Microsoft Word, Excel, emails, including use of internet and online calendar. Level 3 Food Safety and Level 2 Health and Safety. Desirable CriteriaExperience
-
experience within 2 of the following research fields: Programming in Python or Matlab EEG analysis (ERPs and Time Frequency) Machine learning Sleep scoring or analysis of sleep elements (like spindles or Sos
-
machine learning techniques within research computing or data management environments 4. A degree or equivalent experience / professional qualifications 5. An understanding of ITIL service management
-
stakeholders in the School and Student Futures to recommend clear processes enabling the delivery of successful placement and experiential learning activities that meet learning outcomes and professional