Postdoktor i maskinteknik med inriktning mot kunskapsdriven optimering
Core
Developing intelligent, adaptive, and sustainable manufacturing systems using simulation-based optimization, digital twins, and AI-based decision support to enhance operational robustness and resource efficiency.
Role type
Postdoctoral researcher in mechanical engineering (knowledge-driven optimization)
Builds
Resilient and energy-aware production systems for industry, society, and academia
Domain
Manufacturing engineering, industrial optimization, AI, simulation
Deliverable
production ML models | research
Required skills
Simulation-based modeling and optimization of complex industrial systems, Multi-objective optimization, Knowledge-driven optimization, Reinforcement learning, AI-based decision support, Python programming, Machine learning libraries
Preferred skills
Digital twins, Adaptive optimization, Intelligent decision support systems, Industry collaboration, Scientific communication
Technologies
Python, Machine learning libraries, Simulation tools
Responsibilities
Conduct research on optimization and simulation of manufacturing systems, Integrate simulation-based optimization and AI for production planning and scheduling, Publish scientific results
Seniority
Postdoctoral researcher, independent research
