Masterarbeit: KI-Agenten & Simulationsentwicklung
Core
Accelerate model-based simulation development using coordinated AI agents, focusing on Agentic Engineering, controllable agent-based workflows, and local AI models.
Role type
Master's thesis researcher (AI Engineering & Simulation)
Builds
A practical, controllable, and handover-ready approach for AI-supported simulation development
Domain
Industrial automation, engineering simulation, and AI/LLM integration
Deliverable
production ML models
Required skills
Python, LangChain, LangGraph, Prompt Engineering, Open-Source LLMs (Llama, Mistral), Fine-Tuning (PEFT/LoRA), Systematic LLM Evals, Git, Docker, Local Inference Engines (vLLM, Ollama)
Preferred skills
Model-based simulation (Matlab/Simulink, Modelica, FMU), Token efficiency benchmarking, Human-KI interaction design
Technologies
LangChain, LangGraph, Python, Llama, Mistral, PEFT, LoRA, vLLM, Ollama, Matlab/Simulink, Modelica, FMU
Responsibilities
Analyze patterns and anti-patterns in agent-based workflows; Develop a Harness-Engineering approach for structured workflow control; Investigate transition from cloud to local AI models; Evaluate performance regarding token consumption and compute power; Assess UX for integrating simulations with AI agents into production
Seniority
Master's student (6-month project)
