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for applicants to also have: Honours/Masters degree in either Engineering, Computer Science or IT related fields. Experience in Deep Learning, Computer Vision, and Python programming Interest in
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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
ensure local relevance. Required knowledge Artificial Intelligence; Machine Learning; Computer Vision; Bioinformatics; Biomedical Engineering; Neuroscience; Genomics; Medical Physics; Data Science
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content. Similarly, computer vision models are implemented to analyse images and videos for symbols, gestures, or contextual clues associated with radical groups or criminal activities. Multimodal
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would be a plus) Experience in statistics/computer vision/machine learning/robotics Outstanding academic output documented via journal/conference publications in the relevant fields Ability to program
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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education, pursuing their own research project during the mobility period, parallel to joining a research group and having a host supervisor at Lund University. For information about eligibility and selection
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security Experience with medical datasets, medical images, or clinical text Knowledge of explainable AI methods Experience with NLP, computer vision, or multimodal learning Nice to Have Background in digital
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security Experience with medical datasets, medical images, or clinical text Knowledge of explainable AI methods Experience with NLP, computer vision, or multimodal learning Nice to Have Background in digital
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Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering , with demonstrated knowledge in machine learning, algorithms, and programming. Prior exposure to reinforcement learning
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Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering , with demonstrated knowledge in machine learning, algorithms, and programming. Prior exposure to reinforcement learning