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Field
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Learning and Deep Learning libraries (e.g., Pytorch, Tensorflow) will be considered a significant advantage; Previous experience in image processing and\or computer vision will be considered an advantage
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in the relevant field (20%): Mathematical Modelling/ Language Programming/ Digital Signal Processing/ Digital Image Processing/Circuits projects/ Automatic Measurement Systems Composition
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detections of extreme-weather events and subsurface changes, in the seismic zones that affect Kentucky, or their global analogs, and with near-surface imaging for neo-tectonic investigations and other site
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records and medical images, for applications pertaining to patient diagnostics and prognostics. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field
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disease with a focus on Alzheimer’s Disease. Computational models will be developed that utilize data obtained from a wide range of experiments, from basic biochemical methods to advanced imaging techniques
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have experience in routine molecular biology techniques like Western blotting, PCR, immunohistochemistry and/or microscopy. Experience with electrophysiology or live-cell imaging techniques like calcium
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learning and image processing techniques for estimating the onset of arterial disease. 2)Implementation of denoisers as priors for the solution of inverse problems. Implement code in PyTorch and other
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strategies — developing systems that can respond dynamically to neural and behavioral signals in real time. Your Role: Develop and evaluate new methods for optimizing DBS therapy — from imaging and modeling
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the imperial collection (quire structure, copyists, watermarks, ruling), potentially including opera scores from other Viennese sources from the period under investigation; Ordering of digital images
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. Reporting: Communicate findings to project partners with diverse backgrounds (e.g., space systems engineering, astrobiology, microfluidics) to support the development of a prototype LMCOOL instrument for