Job Summary: The Research Fellows will be responsible for undertaking in-depth research in machine learning and big data for the Grab-NUS AI Lab to solve real-world transportation challenges with rigorous research in AI and data science. Phase II of the Grab-NUS AI Lab will focus on computer vision, NLP, and AI explainability. The research should lead to both publications in top-tier international conferences and journals, as well as real-world industry implementations. He/she will be working closely with the Principal Investigator and lab members on one or more research projects together with Grab data scientists on interesting and challenging real world datasets and problem statements.

Responsibilities:

• Design and develop new state-of-the-art algorithms and applications in machine learning and artificial intelligence for the transportation and e-payment domains, with a focus on computer vision, NLP, and AI explainability;
• Write high-quality research papers to be published at top-tier international research venues;
• Contribute to knowledge exchange and technology transfer activities with industry partners and collaborators;
• Develop ideas for application of research outcomes.

Requirements:

• A PhD in Computer Science, with specialization related to machine learning, data mining, artificial intelligence or databases;
• Proven ability to conduct independent research with a strong and relevant publication record (publications in top-tier conferences in Data Mining, Machine Learning, Databases and other relevant areas)
  
• Expertise in computer vision, NLP, or AI explainability; Prior research experience in transportation data analytics would be a plus
  
• Proficiency in large-scale programming systems for big data and AI; Experienced in using the latest machine learning, AI, and big data platforms
• Good oral and written skills in English
• Experienced in working in a team, with people of diverse skillsets, including industry end-users
• Passionate in working with developers and users to get solutions into use.

Job Summary: The Research Assistant will be responsible for data extraction, data standardization and integration, implementations for algorithms and methodologies based on state-of-the-art research in machine learning and big data for collaborative machine learning.

Responsibilities:

• Perform data cleansing and processing for analysis of real-world datasets from transportation and e-payment domains;
• Design and write robust, readable, and reusable code components and applications to implement state-of-the-art research outcomes in machine learning, artificial intelligence, and big data, with a focus on computer vision, NLP, and AI explainability;
• Assists with the editing and preparation of manuscripts, reports and presentations;
• Participate in presentations and demos for exhibiting work at appropriate events.

Requirements:

• Bachelors or Masters in Computer Science with a focus in AI/Machine Learning/Big Data;
• Solid programming and application development skills with experience in Python/Perl/R. Mastery of programming languages such as C/C++/Java, and experience with Tensorflow would be a plus;
  
• Ability to read and understand methodologies in research papers;
  
• Fluent in English and good team-player.