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Job Description
The selected Research Fellow is required to work on a research project related to big data driven vessel risk profile estimation and classification using Artificial Intelligence (AI)-based approaches. The first research focus of this project is to establish a multi-source vessel risk data mall. The multi-source data fusion approach will be conducted to establish a comprehensive vessel risk data mall. Alternatively, the unstructured text data in accident report could be mined with Natural Language Processing (NLP) techniques to validate the performance of our proposed multi-source data fusion method. To reduce the dimensionality and remove redundant information on the vessel risk profile, feature selection methods will also be utilised. The second research focus of this project is to develop an AI-based vessel risk level assessment engine. AI-based vessel risk assessment models will be developed, and the most significant contributing factors to vessel risk level will be identified.
Job Requirements
• Possess a PhD in Transportation and Data Science related subjects.
• Experience in developing/applying data-driven models in transportation research or big-data related project.
• Ability to sophisticatedly use at least one programming language, e.g., Python, R Java, SQL, Julia, C# and C++.
• Excellent written and spoken communication and able to present results clearly.
• Good teamwork and leadership, self-manage and motivated, with minimum supervision.
• Data mining and analysis, machine learning skills.
• Research experience on maritime risk assessment and big AIS data processing.
• Good publication record in international leading journals.
• Open to fixed-term contract. [ Able to commit for at least 8 months – fr Aug 24 to 30 Apr 25 ].
