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, combining both accuracy and explainability; (3) extend statistical learning theory to offer theoretical bounds for intrinsically-aligned AI models; (4) employ the newly-developed metrics to train deep neural
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. The BlueMat project ?Multiscale Operando Super-Resolution Imaging of Water Imbibition in Hierarchically Porous Materials? aims to establish methods for super-resolution imaging using deep learning. You will
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Ulm, Baden W rttemberg | Germany | about 13 hours ago
the contribution of somatic (mosaic) mutations that may occur during development or aging to ALS. To this end, we are offering a PhD position to employ targeted deep sequencing or single cell-resolved detection
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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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Deep brain stimulation (DBS) is a medical therapy for neurological disorders, in which an implanted system provides electrical impulses to dysfunctional brain areas to alleviate patients’ symptoms
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; Machine Learning• Clinical pathways and decision support for patients with acute chest pain• AutoPiX – Explainable Deep Learning for Multimodal and Longitudinal Imaging Biomarkers in Arthritis• Speaking
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the Job related to staff position within a Research Infrastructure? No Offer Description At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and
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position (technician) will focus on performing Raman/FTIR on retrieved samples. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data.
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of short-axis MR image sequences. Training You will be based at the Vision Computing Lab within the School of Computing Sciences, which specializes in deep learning for medical image analysis and neural
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analysis will focus on building sophisticated Deep Learning models, e.g., Long Short-Term Memory (LSTM) networks, to accurately model DPs over time and predict mood deterioration. The project will implement