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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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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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scale, undirected Brownian motion dominates in state-of-the-art membranes. 2D membranes have the potential to overcome this intrinsic deficiency and shift the paradigm of particle transport from
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reference architecture for data visiting. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine
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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
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, productivity, and overall operational stability of the process plants can be determined. This rigorous analysis will provide a clear picture of the flexibility potential and set the stage for implementing
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, including trans-differentiation of fibroblasts into neurons (iNeurons), development and screening of antisense oligonucleotides (AONs), live-cell imaging, and transcriptomic analyses. Laboratory work will