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machine learning, deep learning, audio/image/video classification, attention mechanisms, zero/few shot learning, and evolutionary algorithms. The Research Associate should have proficient programming skills
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. The candidate will be expected to carry out experiments that support the objectives of the research project, such as generating primary neuronal cultures, conducting high-resolution imaging, and performing
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factors assessment). You should hold a relevant PhD/DPhil (or near completion) and have publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a
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. Excellent communication, team working, and organisational skills are essential. Experience using state-of-the-art imaging software, image processing using Matlab or similar image processing platforms is
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of a collaborative team, led by Dr Sarah Morgan at the School of Biomedical Engineering and Imaging Sciences. The School is a world leading centre of expertise in AI for healthcare, providing
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males and females respond differently to bacterial infection. The successful candidate will play a leading role in the imaging and data analysis components of the project. They will develop and apply high
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the analysis of proteomic data, as well as experience in spatial proteomics (laser capture), single cell proteomics and MALDI Imaging. Previous research experience in the genetics of human disease is desirable
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biomarker discovery from the CAIFE image and video dataset. The full-time post is funded by InnoHK and is fixed term for 24 months. About you You will be working in a small highly motivated inter
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, including imaging mass cytometry (IMC) Advanced programming and data analysis skills in R and/or Python Downloading a copy of our Job Description Full details of the role and the skills, knowledge and
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researches the new paradigm of photography embedded in contemporary mobile phone cameras and promoted as “AI-assisted” since 2024. It examines the extractive image processing involved in AI image making