Job Description

JOB DESCRIPTION

At A*STAR, we make it our mission to attract and develop a diversity of talent along the research, innovation and

enterprise value chain, with career paths developed for scientists, engineers and entrepreneurs. In return, we commit to investing in the personal and professional growth of each of our officers.

We are looking for highly motivated individuals who are able to work independently and yet are good team players,

possess excellent research, analytical, technical and problem-solving skills, good technical writing and presentation skills. If you share our interests in solving challenging science and engineering problems, we welcome you to apply.

Successful candidates will be responsible for: * Designing novel algorithms for improving the performance (e.g. accuracy, diversity, explanation and fairness) of various machine learning models and systems

• Using different learning paradigms, e.g. deep and shallow learning frameworks for effectively performing analytical tasks in various data domains(e.g. graph, biology, and text, etc.)
• Preparing high-quality papers for being published in major AI journals and conferences

JOB REQUIREMENTS * PhD Degree in Computer Science or Computer Engineering

• Strong track record of research in AI and related applications (e.g. publications in related journals like TPAMI, TNNLS, TCYB, TEVC, TFUZZ, JMLR and other IEEE or ACM Transactions, conferences like ICML, NeurlPS, ICLR, CVPR,AAAI, and IJCAI)
• Possess research experience in machine learning (e.g. unsupervised or semi-supervised learning), and data mining for real-world data-driven problems
• Strong programming skills or other quantitative skills (e.g. statistical analysis)
• Ability to work both independently and in a team.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.