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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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zebrafish—being small, transparent and responsive to threatening stimuli —enable whole-brain imaging of neuronal activity. This makes them an ideal model to study the neurons involved in these innate
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metabolism and performance. Working across in vivo, ex vivo, and in vitro systems, you will integrate advanced cardiac imaging, metabolic flux analysis, and biochemical profiling to connect molecular damage
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, drying, and curing affect adhesion, mechanics, and wear resistance. Characterize inks using advanced experimental techniques like synchrotron imaging (e.g. at the ESRF in Grenoble), DMA, nanoindentation
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system module and investigate linkages with the more detailed IMAGE model. The project is embedded in the broader EMBRACER programme, which aims to advance our understanding of climate feedbacks. You will
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Analyse rat MRI data, including integration with histology and calcium imaging Combine data across cellular, network, and whole-brain scales, primarily through network science and computational innovations
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to advance 3D imaging methods for neuroscience. Your colleagues: An interdisciplinary team working across the Cognitive Neuroscience Department and the Mental Health and Neuroscience Research Institute
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how intrinsic plasticity contributes to memory encoding and alters cognitive processes. In this project, we will leverage the advanced voltage imaging in larval zebrafish to investigate how intrinsic
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corresponding design flow for such hybrid configurations in the past decade. Based on these models we have developed a prototype focal-plane array that was optimized to provide wide-angle scanning up to +/- 20
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it an advantage if you bring the following: Experience in MRI brain imaging and/or EEG analysis Interviews will take place on December 1st in the afternoon (2:00-4:00 PM) and possibly on December 5th