Research Engineer (1-year contract), SCIS

Singapore Management University; Singapore; Hybrid; SGD 60,000 - 90,000; Full time

Job summary

Singapore Management University is seeking a research-focused candidate to design and develop world models for vehicle routing problems. You will integrate these models with neural solvers and planning methods to drive decision making in complex optimization tasks.

Responsibilities include implementing baselines, evaluating on datasets, and preparing technical documentation and publications. Strong AI foundations and communication skills are essential for collaboration in a small academic team.

Qualifications

• Master degree in Computer Science, Information Technology or Information Systems with AI focus.
• At least one year of research or development experience in reinforcement learning or related areas.
• Knowledge of world models, generative modelling and optimization techniques.
• Ability to design rigorous experiments, benchmarks and reproduce results.
• Strong foundations in algorithms, data structures and mathematical reasoning.
• Publications or substantial project work in AI/optimization are advantageous.
• Clear written and verbal communication; able to work independently in a small research team.

Responsibilities

• Design and develop world models that learn compact representations of VRP states.
• Integrate models with neural solvers, planning, search or RL methods for decision making.
• Implement neural and traditional baselines and evaluate on VRP datasets.
• Prepare research papers, technical documentation and reusable code.
• Undertake other duties as assigned.

Skills

Reinforcement learning

Experiment design

Communication skills

Independent yet collaborative

Graph neural networks

Education

Master's degree in CS/IT/IS

Job description

COMPANY DESCRIPTION

Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together – building a strong collegiality and morale within the university.

Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities – all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.

RESPONSIBILITIES

• This position is forSchool of Computing and Information Systems (SCIS).
• Design and develop world models that learn compact representations of VRP states, transitions and solution trajectories.
• Integrate learned world models with neural solvers, planning, search or reinforcement learning methods for decision-making.
• Implement strong neural and traditional optimization baselines and evaluate them on synthetic and real-world VRP datasets.
• Prepare research papers, technical documentation and reusable code.
• Undertake other duties as assigned.

QUALIFICATIONS

• Minimum master degree in Computer Science, Information Technology, Information Systems or closely related disciplines with particular focus on Artificial Intelligence.
• At least one year of relevant research or development experience in reinforcement learning, combinatorial optimization or a related area.
• Working knowledge of world models, generative modelling, combinatorial optimization, vehicle routing problems,neural solvers or graph neural networks.
• Ability to design rigorous experiments, build benchmarks, analyse results and reproduce research findings.
• Solid foundations in algorithms, data structures and mathematical reasoning.
• Research publications or substantial project experience in AI or optimization are advantageous.
• Clear written and verbal communication skills, including the ability to prepare technical reports and papers. Self-motivated and able to work independently while collaborating effectively in a small academic research team.