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for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models to real-world data (RWD). Create innovative tools and solutions to extract deeper
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. Proficiency in SQL, Python/R, or similar tools; experience with big data platforms , machine learning, and data warehousing. Commitment to quality, integrity, confidentiality and compliance. Excellent
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motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in bioinformatics, deep learning and/or biomedical image and clinical data analysis
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to formulate mathematical models of the problems and develop efficient solution methods, particularly by leveraging techniques from machine learning and operations research. b) The applicants are expected
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learning, and data warehousing. Commitment to quality, integrity, confidentiality and compliance. Excellent leadership, organizational, project management and problem-solving skills. Strong interpersonal
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Data Scientist (Artificial Intelligence). We now invite applications for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models
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considered for appointment at the rank of Post-doctoral Fellow. The appointee will work on a project on promoting students’ self-directed learning and Chinese online reading competencies. He/She will assist
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. Electrical signals captured from the brain of mice while they engage in different behaviors such as perception, learning and execution of tasks, as well as social interactions are analysed using advanced
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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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bioinformatics, deep learning and/or biomedical image and clinical data analysis (e.g. Linux, R programming) is essential. The appointees will need to perform data analysis of single cell RNA-sequencing