4 of 4 Remote/Hybrid Model Validation Jobs in Sheffield

variation in scanners, acquisition protocols and disease phenotypes; undertake quality control and failure analysis; improve segmentation, feature extraction and prediction pipelines; and establish reproducible validation workflows. You will work closely with radiologists, pulmonary vascular clinicians, clinical scientists and statisticians to link RAIDA‐derived imaging biomarkers with right‐heart catheterisation … including appropriate domain‐adaptation, semi‐supervised or related approaches where these add value. Design and perform rigorous training, testing and hold‐out/external validation, including repeatability, calibration, subgroup performance, bias assessment, quantitative segmentation metrics and clinically relevant diagnostic/prognostic performance measures. Undertake systematic image review, quality control ...

systems that recognise known species while handling unseen classes. The role spans the entire research pipeline – from processing spatio-spectral-temporal UAV imagery to model development, algorithm validation and deployment, including contributions to a QGIS forest monitoring plugin. Based in the PRISMA Computer Vision lab within the School … continual learning approaches to improve the robustness, reliability and adaptability of tree species mapping systems. Process and analyse UAV and geospatial data and conduct validation experiments, assessing the performance of developed algorithms using real-world datasets. Contribute to the development of practical software tools, including a QGIS plugin ...

models for respiratory health. You will work with large-scale real-world recordings of speech, breathing and cough, developing self-supervised learning and foundation-model approaches that are robust to noise, demographic variation and different recording environments. You will also contribute to clinically informed acoustic biomarkers … generalisability and clinical utility. Investigate potential confounding factors, demographic bias, background‐noise effects and domain shift, and develop methods that improve trustworthy and equitable model performance. Contribute to clinically informed acoustic modelling, working closely with the Southampton PDRA, who will lead complementary feature‐engineering research; investigate how engineered physiological ...

models for respiratory health. You will work with large-scale real-world recordings of speech, breathing and cough, developing self-supervised learning and foundation-model approaches that are robust to noise, demographic variation and different recording environments. You will also contribute to clinically informed acoustic biomarkers … generalisability and clinical utility. Investigate potential confounding factors, demographic bias, background-noise effects and domain shift, and develop methods that improve trustworthy and equitable model performance. Contribute to clinically informed acoustic modelling, working closely with the Southampton PDRA, who will lead complementary feature-engineering research; investigate how engineered physiological ...