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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
these engagements will be integrated with outputs from advanced AI models (e.g.,geospatial deep learning, graph neural networks, and explainable AI ) to refine the AMR risk maps and ensure local relevance. Required
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; expertise in several of the following: life cycle assessment, life-cycle cost analysis, pavement simulation, machine learning, deep reinforcement learning, and/or physics-informed modeling frameworks; and
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and rigorously evaluating new machine-learning methods. • Excellent Python programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research
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: PhD degree in Computer Science, Computer & Electronics Engineering or other related fields Strong background and knowledge in at least one or preferably more of the following fields: Cybersecurity, Deep
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Biology, Computer Graphics, Computer Vision, Control Systems, Deep Learning, Digital Humans, Earth Observation, Educational Technology, Efficient AI, Explainable AI, Haptics, Human-Computer Interaction
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related to heart failure and cardiovascular biology. Develop and apply machine-learning and deep-learning approaches to identify disease-associated cardiomyocyte subtypes, cellular trajectories, and
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the supervision of the Principal Investigator, including but not limited to the following: Develop new computational tools through the application of AI / deep learning / machine learning / statistics on spatial
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Strong research experience in machine learning or deep learning, with practical experience of developing models in Python using a modern framework such as PyTorch. Essential Application/interview Research
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computer systems is cognitivist in nature. The advancements in LLMs appear promising in bridging this dialogic gap in feedback and learning via computer systems. This study aims to test the efficacy of LLMs
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technical field OR a combination of education and relevant working experience to equal at least four years Strong programming skills in Python. Familiarity with machine learning, deep learning, and