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High Research Impact
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At Social AI Studio, we aim to develop and train the future generation of social AI scientists/designers. Email us your CV!
Postdoctoral Research Fellow: Candidate should have a Ph.D. degree and a promising academic record. Topics considered particularly relevant include social media mining, computational social science, machine learning, deep learning, recommender systems, natural language generation. A strong background in other computational social science, data mining and machine learning topics will also be considered.
Research Engineer: Candidate should have a Bachelor’s and/or Master’s degree in Computer Science or closely-related disciplines. He or she should be competent in at least one programming language and have some experience in implementing data mining algorithms and machine learning models (school projects included).
Master/Ph.D. Student: Candidate should have a Bachelor’s and/or Master’s degree in Computer Science or a closely-related discipline with high academic standing. He or she should be competent in at least one programming language and demonstrate a strong passion for AI and/or computational social science research. We also offer scholarships to outstanding students enrolled in our Ph.D. programs!
Research Intern: Candidate should be currently enrolled in a Bachelor’s and/or Master’s degree in related disciplines. He or she should have a keen interest to learn more about AI and/or computational social science research.
The following funded projects are hiring Postdoctoral Research Fellows, Research Engineers, and Research Interns:
Detecting and Monitoring Hate Speeches in Social Media - This proposal aims to design effective data analytical tools and machine learning algorithms to curb the spread of hate speech on social media. Specifically, we outline two main aims of this project: (i) Develop semi-supervised meta-learning algorithms to detect hate speech on multiple social media platforms. (ii) Designing multilingual analytical monitoring dashboards that monitor hateful social media content across Southeast Asian (SEA), interpreting content in native southeast Asian languages.
Memenlytics: Understanding Memes in Social Media - The proposed project aims to improve our understanding of memes shared in online communities. More specifically, the project aims to design state-of-the-art deep learning algorithms and analytical tools that enable large-scale analysis of online memes. In addition, the developed algorithms and analytical tools will also support the analysis of memes based on Singapore context (e.g., expressing views towards Singapore government bodies and policies).
Authorship Attribution on the Web - Authorship attribution (AA) is the task of determining the writer of an article. This proposed project aims to develop AA technologies for the content shared online. Specifically, the project aims to design state-of-the-art deep learning algorithms accompanied with analytical tools that empower analysts to perform AA on large-scale generated content. Besides making technical contributions, we aim to provide insights to empower analysts and platform providers to sieve out sock puppets from authentic authors. These new insights enabled by our developed AA techniques can also be used to design policies to foster a more cohesive online community.