-
, integrate device engineering with clinical workflows, and apply artificial intelligence and machine learning for automated image and signal analysis, tissue classification, and real-time diagnostics
-
sophisticated machine learning tools for image processing Experience in mathematical modelling Knowledge in comparative neuroscience (comparative vertebrate neuro) Proficiency in basic computer packages (eg
-
, including clinical translation to benefit patients. The Programme is mainly hosted by the Research Department of Imaging Chemistry and Biology within the School of Biomedical Engineering & Imaging Sciences
-
biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a multidisciplinary team at KCL, UCL and clinicians at Great Ormond Street
-
. The broader goal of the overall programme, funded through the Wellcome Trust bioimaging technology development initiative, is to deliver multimodal datasets in an interoperable manner through open access