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Field
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supporting documentation, proven experience in all of the following areas: natural language processing and machine translation (sequence-to-sequence modelling, NMT, glosses); deep learning, Transformers, and
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, simulation, and data-driven methods to support secure, reliable, affordable, and sustainable power systems under deep decarbonisation, increasing renewable uncertainty, and the growing participation
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) validation and extension of models for the prediction of enzyme-substrate interactions; (iv) integration of the previous models into deep learning pipelines for retrobiosynthesis. Applicable legislation and
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to clinical natural language processing. With training and experience in the use of deep learning and large language models, specifically in problems related to clinical natural language processing. Self
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measurement science research in robotics, advanced autonomy, and artificial intelligence systems. Utilizing deep learning, large language models (LLMs), reinforcement learning, and unsupervised machine learning
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excellence across CEPS. You will contribute to CEPS’ visibility and influence through public speaking, media engagement and thought leadership activities. Where to apply Website https://cdn.ceps.eu/2026/07
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and Machine Learning/Deep Learning Applications for Low Amplitude Transient Signal extraction: this project explores the use of AI, ML/DL techniques to explores several sources of signals with
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leader • Excellent written and oral communication skills Preferred Qualifications • Background in antisemitism studies • Experience with R, NLP and deep learning libraries • High performance computing
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications
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sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve