Job Openings (SG)

Multiple Postdoctoral Research Fellow and Research Assistant Openings for Toward Trustable Model-centric Sharing for Collaborative Machine Learning

We are looking for multiple Research Fellows and Research Assistants to participate in a new project entitled “Toward Trustable Model-centric Sharing for Collaborative Machine Learning” at the Institute of Data Science and the School of Computing, National University of Singapore. The project is funded under the prestigious AI Research Programme by AI Singapore, led by Professors See-Kiong Ng, He Bingsheng, Wynne Hsu, Lee Mong-li, Vincent Tan, and Warren Chik (SMU) in collaboration with renowned AI researchers such as Professors Dawn Song (UC Berkeley), Patrick Jaillet (MIT), Bryan Low (NUS), Sinno Pan (NTU) and Dr Nghia Hoang (IBM Research). Interested individual please send your cover letter and resume to email seekiong@nus.edu.sg.

 

Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on trusted collaborative machine learning that lead to publications in top-tier international conferences and journals, as well as real-world implementations.

Responsibilities:

  • Develop new concepts and algorithms in data science, machine learning, and artificial intelligence for trusted collaborative machine learning;
  • Be up-to-date on state-of-the-art methodologies in related technical fields and application domains;
  • Develop ideas for application of research outcomes;
  • Contribute to knowledge exchange activities with external partners and collaborators;

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;
  • Prior experience in federated learning, Bayesian optimization, or privacy/security research in data sharing would be a plus;
  • Experienced in using the latest machine learning, AI, and big data platforms;
  • Excellent interpersonal communication and oral presentation skills in English

Job Summary: The Research Assistant will be responsible for designing and implementing efficient and robust systems, and applications for algorithms and methodologies based on state-of-the-art research in machine learning and big data for collaborative machine learning.

Responsibilities:

  • 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;
  • Perform data cleansing and processing for analysis of real-world datasets;
  • 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;