Contract until March 2027
As a Research Engineer, you will support the design, development, and implementation of mobility and transportation simulation solutions, digital twin platforms, and AI-driven optimization technologies. The role focuses on addressing urban mobility, logistics, and infrastructure challenges through simulation modeling, software development, data analysis, and AI integration.
Key Responsibilities
- Develop and configure mesoscopic and microscopic simulation models.
- Design simulation workflows, application logic, and system behavior models.
- Build software modules for simulation execution, analysis, and visualization.
- Process, analyze, validate, and optimize simulation data and results.
- Conduct testing, debugging, and troubleshooting to ensure system reliability.
- Support prototype development, demonstrations, and research exhibitions.
- Collaborate with multidisciplinary teams on solution design and implementation.
- Integrate AI/ML models into simulation and optimization workflows.
- Maintain documentation, version control, and development records.
Required Skills & Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Industrial Engineering, Transportation Engineering, Civil Engineering, Data Science, Applied Mathematics, or a related discipline.
- Fresh graduates are welcome to apply if they have done some relevant projects, 2 years of experience is an advantage.
- Experience with simulation tools (e.g., AnyLogic) and simulation methodologies such as discrete-event and agent-based modeling.
- Proficiency in Java and Python.
- Knowledge of GIS tools (ArcGIS, QGIS) and geospatial data formats (OpenStreetMap, GeoJSON, Shapefile).
- Experience with web application development, APIs, and system integration.
- Strong analytical, problem-solving, and debugging skills.
- Good communication skills and ability to work in a collaborative research environment.
Ideal Candidate
A technically strong engineer with an interest in transportation systems, smart cities, digital twins, simulation technologies, AI/ML, and data-driven optimization, capable of turning research concepts into practical, real-world solutions.