School of Accounting and Finance
Senior Research Fellow / Research Fellow / Research Associate / Research Assistant
(Ref. 260126005)
1) Senior Research Fellow / Research Fellow
2) Research Associate (two posts)
3) Research Assistant
[Appointment period: each for twelve months]
Duties
The appointees will assist the project leader in the research project – “STA AI simulation algorithm research project - AI multiple strategy simulated fund manager”.
For the appointed Senior Research Fellow and Research Fellow, he/she will serve as the Research Lead for next-generation quantitative trading systems initiative. He/she will be responsible for the technical vision, architecture, and execution of a research project aimed at building a high-performance, low-latency algorithmic execution engine. The roles are designed for seasoned professionals who can blend deep technical expertise in systems programming with a strategic understanding of quantitative finance, driving the project from concept to a robust, research-backed prototype. He/she will take up the following key research and leadership responsibilities:
a) Technical Leadership and Project Management: Provide end-to-end technical leadership for the research project, define system architecture, set development priorities, manage timelines, and ensure the delivery of high-impact research outputs;
b) Core System Research and Development: Lead the design and hands-on development of the algorithmic execution engine, setting standards for code quality, performance, and reliability;
c) Advanced Data Architecture: Spearhead the research and implementation of high-performance databases or similar technologies, ensuring they meet the low-latency demands of intraday trading;
d) Performance Optimisation Research: Direct the systematic profiling and optimisation of the entire trading stack, from market data ingestion to order execution, translating research findings into tangible performance gains; and
e) Collaboration and Mentorship: Act as the primary technical liaison with quantitative researchers, mentor junior researchers, and foster a collaborative, high-output research environment.
For the appointed Research Associate and Research Assistant, under the guidance of senior researchers, they will contribute to innovative research on the design, optimisation, and evaluation of algorithmic trading systems. This role offers an exceptional opportunity to apply rigorous programming and analytical skills to advance the state-of-the-art in quantitative finance. They will take up the following key research responsibilities:
a) System Design and Experimental Implementation: Participate in the design and implementation of experimental trading system modules to test novel algorithmic ideas and architectural improvements;
b) Data Analysis and Computational Research: Process and analyse large-scale financial market data using advanced databases, develop scripts for quantitative analysis and to support empirical research hypotheses;
c) Performance Evaluation and Benchmarking: Conduct controlled experiments to profile system performance, compare algorithmic benchmarks, and analyse latency and throughput characteristics;
d) Collaborative Research and Documentation: Work within a research team to prototype trading strategies, document methodology and findings, and contribute to academic or technical publications; and
e) Technology Investigation: Research and evaluate emerging open-source tools, frameworks, and technologies relevant to high-performance trading systems.
Qualifications
For the post of Senior Research Fellow, applicants should have a doctoral degree with at least six years of postdoctoral research experience or equivalent qualifications and experience.
For the post of Research Fellow, applicants should have a doctoral degree plus at least three years of postdoctoral research experience or equivalent qualifications and experience.
Applicants for the posts of Senior Research Fellow and Research Fellow should also possess one of the following requirements:
a) Academic Credentials and Working Experience: A doctoral degree or an equivalent qualification in Computer Science, Financial Engineering, Mathematics, or a closely related field, plus a minimum of 5 years of working experience in global prestigious investment banks or as asset managers;
b) Proven Leadership: Accomplished and leadership-oriented. Demonstrated experience leading a technical project or team, with the ability to make architectural decisions, manage technical debt, and guide collaborative research;
c) Quantitative Finance Domain Knowledge: A solid understanding of financial markets, trading concepts, and the ecosystem. Direct experience in developing systems for trading, risk, or analytics is required; and
d) Technical Acumen: Outstanding knowledge of data structures, algorithms, network programming, and Linux/Unix systems. A proven track record of solving complex performance and reliability challenges.
e) Preference will be given to those with:
i) Elite Industry Background: Professional experience at a global, prestigious investment bank, hedge fund, or as asset manager is a significant advantage;
ii) Specific Technology Expertise: Hands-on experience with DolphinDB, kdb+, or similar high-frequency time-series databases; and
iii) Market Knowledge: Practical understanding of A-share market micro-structure, exchange connectivity, and order types.
For the posts of Research Associate, applicants should have a master’s degree in Computer Science, Computational Finance, Mathematics or a related field, or a good honours degree in any of the abovementioned disciplines with at least three years of research/relevant work experience.
For the post of Research Assistant, applicants should have an honours degree in Computer Science, Computational Finance, Mathematics or a related field, or an equivalent qualification in any of the abovementioned disciplines.
Applicants for the posts of Research Associate and Research Assistant should also fullfill one of the following requirements:
a) Have strong foundation in systems programming, with proficiency in C++. Familiarity with Rust is a strong advantage;
b) Have at least 1 year of hands-on project experience in a research, academic, or development setting;
c) Be motivated and willing to quickly learn and apply new database technologies, with a strong interest in FinTech and low-latency systems research. Experience with time-series databases or high-performance computing is preferred;
d) Have a solid understanding of data structures, algorithms, and basic operating system/network principles; and
e) Have a proactive research mindset, strong learning ability, and excellent collaboration skills.
f) Preference will be given to those with:
i) Demonstrated interest in financial markets and quantitative trading research;
ii) Experience in network programming, concurrent systems, or Linux-based development environments; and
iii) Previous exposure to academic or industrial research processes, including experiment design and technical writing.
Applicants are invited to contact Dr Walter Yao via email at walter-x.yao@polyu.edu.hk for further information.
Conditions of Service
A highly competitive remuneration package will be offered.
Consideration of applications will commence on 2 February 2026 until the positions are filled.
Posting date: 26 January 2026