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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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We seek to recruit a Research Associate/Fellow to join our team developing a groundbreaking technique based on autofluorescence (AF) imaging and Raman spectroscopy for detection of positive lymph
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working with Prof. George Chen. Join a multi-disciplinary team at the TDHVL that includes academic staff, postdoctoral researchers, engineers, PhD and undergraduate students. For further details on our
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/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
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animal models. The work will include: Biochemical Analyses: Investigating molecular pathways and biomarkers. Cell Culture and Imaging: Utilizing cell and tissue imaging techniques to study mechanisms
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. The Research Fellow will join an international team in the project “Imaging the magma storage region and hydrothermal system of an active arc volcano”, funded by the UK Natural Environment Research Council and
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online behaviour at scale, across multiple modes of communication (messages, images, video, memes and emojis) that shape participation and meaning in warfare. You will lead and manage a range of individual
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Please apply online and attach your resume (including a list of two referees), and a separate cover letter that outlines how you meet the selection criteria below: Essential Selection Criteria: PhD in
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
to Apply Please apply online and attach your resume (including a list of two referees), and a separate cover letter that outlines how you meet the selection criteria below: Essential Selection Criteria: PhD
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years of completing their PhD, although career breaks for parental leave and/or health reasons will be considered. This is because the roles are aimed at early career academics who would benefit from a