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during pathological conditions. 2. Neonatal seizures and epilepsy 3. GABAA receptor physiology. We approach these research areas with electrophysiological and imaging. The Postdoctoral researcher will be
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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors
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, including patch-clamp electrophysiology, high-resolution imaging, chemogenetic manipulation of glial activity, and behavioral assays in rodent models Analyze and interpret complex datasets from
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THR demand in younger patients expected to increase fivefold by 2030, revision surgeries will also rise. To improve implant positioning, image-guided navigation is increasingly used in complex THR
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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concerned, among other things, with the effects of images and the mechanisms that make up communication with images. Key questions are: Who produces images and for whom? What message do these images convey
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, patch clamp recording, confocal microscopy, calcium imaging and other biochemical analysis (western blot, ELISA, etc.). Ability to work independently and collaboratively in a team environment Excellent
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heterogeneity; namely non-iid and domain shift, e.g. multi-modal data acquired by different scanners and imaging protocols. Publish and present scientific results at international conferences and high-impact
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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more sensitive and faster cancer imaging. This PhD project will focus on surface functionalisation of metascintillators to optimise their scintillation performance, light yield, timing resolution, and