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Field
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engineering disciplines, including structural mechanics, hydrodynamics and machine learning Strong programming skills in Python and/or MATLAB Experience with scientific computing, CFD/FEM software, potential
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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of three work years of the total term period must be dedicated to doctoral work.) For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Engineering
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
- SIPG LAB/ISR and 1801P.01460.1.04 LARSYS/ISR BASE 2025-2029 – SIPG LAB/ISR, financed by national funds through FCT/MCTES Workplan: Develop new representations for computer vision and machine learning
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selection criteria Knowledge/experience with control engineering, information fusion and/or data assimilation, marine technology Knowledge of and hands-on experience with machine learning and/or statistical
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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, relating to craniofacial identification research and machine learning. You will require a computer science background. You will be applying AI and/or machine learning to Face Lab processes in relation
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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learning, computer vision, or a related field; knowledge of affective computing, generative AI models, and deep-learning methods; proficiency in Python and experience with machine-learning libraries