Top Research Jobs in Singapore

Develop modern C++ systems for systematic investing, including low-latency data processing, high-frequency trading execution, quantitative analytics libraries, and machine-learning inference tools. Collaborate with quantitative researchers to build scalable, reliable, and performant production platforms, design distributed data pipelines, evaluate system architectures, and maintain fail-safe live-market trading infrastructure.

Research and assess Asia-based fund managers, investment strategies, and managed products. Lead manager interviews, develop rating notes and research reports, formulate investment opinions, contribute to thought leadership, and help shape research methodologies. The role also involves analytical assignments, stakeholder engagement, administrative work, and collaboration with global investment, research, data, and software teams.

Conduct ML/DL research to develop predictive models from large market datasets, integrate models into systematic trading strategies, contribute to AI/ML libraries, and deploy production algo systems with P&L responsibility across FX, Rates, Commodities, and Credit.

Develop mathematical models and trading strategies, back test trading models, conduct research and statistical analysis for monetization systems.

As a Quantitative Research Analyst Intern, you will develop and improve trading models, conduct statistical analysis, and collaborate with team members in a data-driven environment.

Quantitative Researchers work on developing mathematical models, backtesting trading strategies, and conducting statistical analysis, utilizing complex data sets and algorithms.

The role involves developing and improving mathematical models for trading, analyzing statistical data, backtesting trading models, and using unconventional data for insights.

Design, develop, and deploy software solutions for automated trading systems while collaborating with researchers on technology priorities.

Join a cross-asset front-office quant trading team to design and implement algorithmic execution strategies, back-test models and signals, develop low-latency infrastructure and transaction-cost-analysis models, and perform statistical analysis to optimize client execution.

Join a front-office quantitative trading team to design and implement algorithmic execution strategies, back-test models and signals, build low-latency trading tools, and run real-time and post-trade transaction cost analysis to optimize execution.

Develop and maintain mathematical models and trading algorithms for valuation, hedging, risk measurement, and electronic trading in commodities. Collaborate with trading desks, product managers, technology, and control functions to implement production-ready models, ensure regulatory compliance, and support quantitative innovation and portfolio risk methods.

Participate in semiconductor technology research and development projects: perform experiments, data analysis, modelling/simulation, and device characterization; generate technical reports, recommendations, and present findings. Leverage AI/ML and advanced analytics where applicable and collaborate with engineers to support process integration and next-generation memory technology development.

Quantitative Research Engineers at Citadel's GQS develop software solutions, enhance trading systems, and collaborate with researchers to apply quantitative techniques.

The intern will develop trading strategies, back test models, analyze data, and collaborate with the research team to innovate and refine monetization systems.

Conduct research, statistical analyses, and develop automated trading strategies using large data sets and sophisticated statistical techniques.

The Quantitative Research Analyst will develop and test trading strategies, implement models, and conduct statistical analysis in financial markets.

Own and execute the product strategy for Aurora's Wider Asia software offering. Define vision, prioritize roadmap and backlog, specify UI and modelling requirements, collaborate with cross-functional technical and commercial teams, manage client relationships and feedback, and mentor regional stakeholders to drive product delivery across APAC.

Conduct research on next-generation video generation models, focusing on distillation, inference efficiency, reward modeling, preference optimization, evaluation, and scalable training infrastructure. Interns will formulate hypotheses, run large-scale experiments, analyze results, develop research tooling, and communicate findings through reports, presentations, demonstrations, and potential conference submissions under senior mentorship.

Conduct research on 3D reconstruction, focusing on advanced 3D Gaussian Splatting for dynamic and streaming scenarios. Design and implement algorithms for efficient, high-fidelity 3D scene reconstruction and representation in embodied environments. Responsibilities include data collection and processing, experimentation, results analysis, and general laboratory support.

Conduct research and development in computer vision, multimodal learning, medical and industrial imaging, and related AI applications. Design, train, and evaluate deep learning models using Python and PyTorch; curate datasets; perform experiments and analyze results. Review literature, identify research opportunities, contribute to papers, reports, presentations, and code, and collaborate with the principal investigator and multidisciplinary research teams.

Conduct research on efficient, scalable systems for multi-agent AI and HPC workflows. Responsibilities include workload analysis, system prototyping, benchmarking, performance optimization, and experimental validation on supercomputing platforms. The role involves collaborating with faculty and domain scientists, developing innovative technical solutions, and contributing to research papers, reports, presentations, and conference or journal submissions.

Conduct literature reviews and quantitative and qualitative research on the reliability of an AI-powered tagging system for digital portfolios. Analyze research data using SPSS and NVivo, support publications, reports, and presentations, and complete administrative duties for the Principal Investigator. The role requires strong critical thinking, communication, writing, organization, and collaboration skills in an academic research environment.

Develop tools and infrastructure for training language models in interactive environments, implement novel methods in language modeling, reinforcement learning and multi-agent systems, and contribute to publications and open-source projects.

Lead and mentor a research team developing agentic AI (planning, RL, LLMs, diffusion, multi-agent systems). Define and execute research strategy, track state-of-the-art work, and build external AI community relationships to position Skyfall as a research leader.

Conduct research to advance agentic systems by developing methods for planning, reasoning, and reinforcement learning with LLMs and multi-agent systems. Design experiments, build datasets, and stay current with academic advances to improve LLM performance in complex workflows.