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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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interdisciplinary team will develop a machine learning based monitoring system that leverages spoken language processing (SLP) and natural language processing (NLP) of speech recorded at home to calculate relapse
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into products and services for Continental through close collaboration with its business units. Key Responsibilities: To independently undertake research in artificial intelligence, machine learning system, edge
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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Responsibilities: To perform pioneer research in scent digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community
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network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or
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leadership and expertise in the synthesis and characterization of advanced nanomaterials, specifically focusing on the integration of machine learning, wafer-scale synthesis of materials, and high-throughput