Senior Research Assistant

Job Req ID:  1092
Employee Category:  Research
Department:  SCI,MATH & Technology

Job Title: Senior Research Assistant - Integrating Parrondo's Paradox with AI Techniques

Job Description:

We are seeking a Senior Research Assistant to work on a project that integrates Parrondo's Paradox with AI techniques. The successful candidate will develop machine learning algorithms based on the paradox, investigate its behavior in different domains, and develop applications in real-world problems such as portfolio optimization, resource allocation, and control systems. This project aims to uncover the potential of Parrondo's Paradox as a powerful learning algorithm in the context of AI. The successful candidate will work with a team of researchers to explore the paradox's applications in various domains and develop novel machine learning algorithms that can outperform existing methods.



- Develop novel machine learning algorithms based on Parrondo's Paradox

- Investigate the paradox's behavior in different domains, including finance, engineering, and biology

- Develop applications of Parrondo's Paradox in real-world problems, such as portfolio optimization, resource allocation, and control systems

- Collaborate with the research team to present findings in conferences and publications

- Participate in brainstorming of ideas and assist in grants preparation



- Master in Computer Science, Mathematics, Physics, Engineering, or related fields

- Strong background in game theory, probability theory, and statistical analysis

- Experience in developing and implementing machine learning algorithms

- Strong programming skills in Python, R, or MATLAB

- Excellent written and oral communication skills in English

- Strong track record of publications in peer-reviewed journals

We offer a competitive salary and benefits package, as well as opportunities for professional development and career advancement. To apply, please submit a cover letter, CV, research statement to Assistant Professor CHEONG Kang Hao with contact information for three references. Review of applications will begin immediately and continue until the position is filled.


Only shortlisted candidates will be contacted.