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representation for multi-model fusion”. Qualifications Applicants for the Postdoctoral Fellow post should have a PhD degree in Computer Science, Electrical and Computer Engineering or a related discipline or an
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, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large
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qualification; (ii) demonstrate research skills in imaging science and machine learning, particularly on image reverse engineering, fake image and video detection, statistical detection models and mathematical
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strong publication record (first-author papers in high-impact journals preferred). Demonstrated expertise in at least two of the following areas: AI/machine learning for biological modeling (e.g., virtual
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teaching duties. Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information Systems, or a related field, and sufficiently demonstrate abilities to conduct high-quality
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teaching duties. Applicants should possess a PhD degree in Computer Science, Computer Engineering, Information Systems, or a related field, and sufficiently demonstrate abilities to conduct high-quality
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at least two of the following areas: AI/machine learning for biological modeling (e.g., virtual cell, foundation models, graph neural networks, or multimodal omics integration). Epigenetics (DNA methylation
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., MATLAB, Python) is required. Experience with machine learning is highly preferred. Ability to work independently and as part of a team. Key Requirements for PhD: Hold a Bachelor's degree with outstanding
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English. Preference will be given to those with (i) strong background in quantitative methods, geospatial methods, AI and machine learning; (ii) experience in high-performance and cloud computing; (iii
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proficiency in machine learning, statistical modeling, and data analysis using Python, R, or similar platforms. Experience in grant proposal writing, scholarly manuscript preparation, and psychological