PhD Researcher in Data Driven Modelling (Remote, International)

Job summary

This PhD position focuses on data driven modelling, characterization, and optimization of dry forming processes for natural fiber materials, aimed at sustainable production in packaging applications. The role is part of a collaborative doctoral network involving multiple universities and industry partners.

Qualifications

• Completed Master's degree or equivalent by the start date (after January 2026).
• No prior doctoral degree.
• Must comply with mobility rules regarding residency in the recruiting country.

Responsibilities

• Develop and validate data driven models for high-speed dry thermoforming of natural fiber materials.
• Characterize airlaid and fluff pulp forming processes using techniques like X-ray Tomography.
• Optimize thermoforming processes and implement closed loop control in collaboration with industry partners.
• Position scientific work within existing literature and publish findings in peer-reviewed journals.

Skills

• Strong background in production engineering or related fields.
• Knowledge of manufacturing systems and natural fiber materials.
• Experience with manufacturing metrology and programming tools, especially MATLAB.
• Familiarity with Machine Learning techniques is advantageous.
• Strong analytical and communication skills in English.

Education

• A two-year Master's degree (120 ECTS points) in Mechanical, Production, Materials, Chemical Engineering, Computer Science, or a related discipline.

Tools

• X-ray Tomography, MATLAB, and other manufacturing and data analysis tools.