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Field
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computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry
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with remote sensing data (satellite, aerial, hyperspectral, SAR, LiDAR) Computer Vision Natural Language Processing Remote Sensing Machine Learening and Deep Learning Reinforcement Learning Large
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machine learning (including deep learning and/or reinforcement learning) numerical simulation of quantum dynamics Proven programming skills (e.g., Python/Julia/C++), including experience with scientific
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intelligence. Strong knowledge and research outputs in AI, particularly in the field of deep learning, knowledge representation and reasoning, or neuro-symbolic AI. Proven commitment to proactively keeping up
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Computer Science/EEE specializing in Learning Analytics (LA)/Machine Learning (ML) Skills in Learning Analytics (LA) / Machine Learning (ML) field Experience in software development life cycle and programming
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Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), particularly in Natural Language Processing (NLP) and Computer Vision (CV) Familiarity with genomic and bioinformatic databases
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and management, machine and deep learning, as well as a solid understanding of wave phenomena and geophysical data analysis and imaging.
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setup, validate results using electrophysiological recordings, apply deep-learning approaches to analyse noisy data, and disseminate your findings through publications. The team – You will work with the
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow, Machine Learning Department Cooper Laboratory | Department of Orthopaedics | Faculty of Medicine (Anthony Cooper
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or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the