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Field
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technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques
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particular focus on how vocational education across Europe shapes young people’s civic knowledge, attitudes, and engagement. Advanced data analysis: Applying methods such as IRT, SEM, and MG-CFA, using R
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software packages (e.g. Stata, SAS, R). Be expected both to support externally funded research projects, including clinical trials working in collbaoration with the UKCRC-registered Peninsula Clinical Trials
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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About the role - The candidate will focus on Gage Repeatability & Reproducibility (Gage R&R) validation of a new video scope inspection system for turbine blade assessment. The objective is to
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expertise in analysing quantitative datasets (in SPSS and/or R) Evidence of excellent oral and written communication skills Evidence of research productivity, such as writing papers for publication or report
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with children. Experience working with and communicating effectively to populations with intellectual disability. Proficiency in statistical analysis (SPSS, R, or equivalent). Strong communication skills
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, Management Science or closely related field. Experience of designing and performing data analyses. Excellent programming skills in Python or R. Excellent written and verbal communication skills. Demonstrated
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statistics, and update skills in line with advances in the relevant subject area. Teaching: Coordinate R training for statisticians in the group. Plan and deliver training to other members of the trial unit
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modelling; Strong analytical and programming skills (preferably in R and/or python); Presented research findings both internally and at international meetings; Demonstrated ability to publish research in