Promotion - Intelligente Nutzung und Verarbeitung technischer Kunststoffströme – Methodenentwicklung und Validierung am Beispiel von Altfahrzeugteilen
Core
Develop a data-driven methodology and validate it using technical plastic parts from end-of-life vehicles to optimize the use, combination, and recycling of plastic streams.
Role type
PhD Researcher (Materials Science & Data Engineering)
Builds
Data models, AI-driven evaluation models, and validated methodologies for plastic stream management.
Domain
Circular economy, plastic recycling, data science, materials engineering.
Deliverable
research
Required skills
Materials science, data engineering, Python, machine learning, database management, uncertainty/robustness assessment, material characterization.
Preferred skills
Compound evaluation, material mixing scenario assessment, statistical estimation, experimental research.
Technologies
Python, machine learning, databases, data pipelines.
Responsibilities
Develop and validate a scientific methodology for data-based decisions on plastic stream usage; harmonize internal and external data into a model; generate virtual scenarios for material separation and mixing; evaluate material scenarios for process stability and quality; determine data needs and assess characterization methods; collaborate with experts and publish results.
Seniority
PhD Candidate
