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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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II is looking for a part-time (30 hours per week) PhD-Position: Machine Learning / Medical Imaging (m/f/x) (with immediate effect). This position is offered for a duration of 3 years. Join the AICARD
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Advanced Grant to determine the optimal combination of epitopes that elicits the highest level of protection. Within the research group, we value a positive work environment built on respect and
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retention in the seed establishment niche. This project is part of the Indigenous-led ARC Industrial Transformation and Training Centre for Healing Country, therefore, the successful candidate will codesign
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Research, has formed a dedicated doctoral training unit (DTU) on “Forest function under stress” (FORFUS). It consists of 4 inter-linked research clusters, focusing on below-ground processes, tree and canopy
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trapping and analysis using state-of-the-art nanopore experiments. About the Project Our group has pioneered the development of the Nanopore Electro-Osmotic Trap (NEOtrap), a groundbreaking technique that
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You will lead the qualitative work to understand how individuals experienced the intervention and app how it worked. This will directly impact the design and refinement of the intervention, and so
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research methods and data analysis. Ability to work in an interdisciplinary, international team. Excellent command of written and spoken English (Dutch is an advantage). Strong academic writing skills and
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robust and close interaction with the world around us – globally, nationally and locally – we shall be instrumental in building a society based on knowledge, skills and attitudes. Do you want to take part
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning