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research areas: - Inorganic/Materials Chemistry: Focus areas include metal complexes, quantum dots, and clusters for molecular activation and recognition; bioinorganic structures; and multi-modal contrast
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(b) experience in data processing and cleaning as well as conducting regression analysis using Python or Stata. Preference will be given to those with prior knowledge of machine learning techniques
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three or more years of relevant research experience. Preference will be given to those with hands-on experience in laboratory research and data analysis. Applicants are invited to contact Prof. Chien-Ling
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implement user interface (UI) and user experience (UX) elements for creating intuitive and engaging assessment experience to the users; (g) conduct frontend development using modern web technologies
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be given to those with work experience in data collection, liaison with non-governmental organisations, qualitative and quantitative data analysis as well as other research supporting work. Applicants
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design, manufacturing and automation or a related discipline, with experience in data science, coding, image analysis, and statistical analysis. Previous research work experience in ophthalmology/visual
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of the project; (e) assist with data entry, analysis and management of project data; (f) assist in preparing work roster for volunteers; (g) assist in preparing progress and final reports of the project
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- “From waste tires to value-added products: novel valorization process design, simulation, optimization and analysis”. Qualifications Applicants should: (a) have a doctoral degree or an equivalent
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to the following: SDSC6012 – Time Series and Recurrent Neural Networks SDSC6016 – Predictive Analytics and Financial Applications SDSC8013 – Statistical Methods for Categorical Data Analysis (For detailed course
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mechanical engineering, ophthalmology and visual sciences, mechanical design, manufacturing and automation or a related discipline, with experience in data science, coding, image analysis, and statistical