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course development at first and second-cycle levels related to AI (with and without ties to cybersecurity), particularly deep learning, generative AI, large multimodal models, diffusion models and deep
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for supply chain and marketing optimization. The project will integrate machine learning, deep learning, foundation models, and interpretable AI approaches, ensuring scalability, robustness, and industrial
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analysis in cryo-electron tomography data, applied to chromatin organization and synaptic molecular targets. Please include a cover letter with your application. Describe a deep learning project you have
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the competent authority of the Ministry of Higher Education, Research and Innovation (MESR). "Video content security in a deep learning coding architecture" Over the past few decades, numerous video compression
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letter with your application. Describe a deep learning project you have executed, ideally involving 3D image analysis, inverse problems, or physics-informed modeling. Cryo-EM/ET and computational
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Deployment Strategies - Model Compression: Investigate techniques such as quantization, pruning, and knowledge distillation to reduce the computational and memory footprint of deep learning models without
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authority and leadership capability to drive meaningful change. You will bring: A PhD or equivalent qualification, with a distinguished record of leadership in teaching and learning at the tertiary level. An
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/housing allowance and other subsidies. Further details on our package are available at: https://career.admo.um.edu.mo/learn-more/ . Application Procedure Applicants should visit https
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to the body of knowledge in policing. What we’re looking for: A PhD or equivalent qualification in a relevant field. Experience in University-level teaching and learning activities. A record of contributing to
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/deploying deep learning models and machine learning applications. Computer skills: Python (PyTorch, TensorFlow), databases (MySQL), 3D Slicer, ITK-SNAP, OpenCarp. Previous experience in research activity in