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. PhD Candidate Neuroimaging in Epilepsy Our goal: to leverage advanced Magnetic Resonance Imaging (MRI) techniques (including functional MRI to assess brain network metrics and MR spectroscopy to measure
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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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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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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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-driven strategizing and tooling. Prototype, test, and refine existing and new value-driven tools for collective strategizing. Conduct interviews, workshops, and co-design sessions to study collective
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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
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]. You will test prototype designs with elite cyclists and handcycle users to evaluate improvements in performance. During your PhD, your research will be at the intersection of biomechanics, muscle
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GenAI for reproducing, modularizing and FAIR publication of existing research. The reproducibility of scientific findings often depends on access to workflows and code used in original analyses. However
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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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of brain imaging and contribute to insights that can improve healthcare practice. Technical PhD Candidate In this role, you will be responsible for developing and refining MRI technologies to visualize brain