PhD Candidate in Data-driven Micro Manufacturing

Job summary

This PhD position focuses on developing a digitalized, data-driven micromanufacturing process chain for thermoplastic microfluidic diagnostic systems, integrating micro 3D printing and micro injection molding. The role involves experimental processing, material characterization, simulation, and in-situ process monitoring, with a strong emphasis on sustainability in production.

Qualifications

• A two-year master's degree in mechanical engineering, materials engineering, polymer engineering, manufacturing engineering, or a related field.
• Strong foundation in materials processing, polymer materials, or manufacturing technologies.
• Experience with experimental laboratory work and data analysis.
• Interest in numerical simulation and/or process modeling.
• Excellent communication skills in English, both written and spoken.

Responsibilities

• Develop a fully digitalized micromanufacturing process chain by integrating micro 3D printing and micro injection molding.
• Create digital dataflows linking micro 3D printing, micro injection molding, simulation tools, and optical quality control.
• Implement in situ process monitoring and analyze real-time sensor data.
• Optimize processing parameters using modeling and data-driven approaches.
• Validate models through iterative comparison with experiments and uncertainty quantification.
• Collaborate with industrial and academic partners to enable the implementation of micro manufacturing solutions.

Skills

• Proficiency in experimental polymer processing and micro engineering.
• Knowledge of digital manufacturing and simulation technologies.
• Ability to work independently and collaboratively in a multidisciplinary environment.

Education

• Required: Two-year master's degree (120 ECTS points) in relevant engineering fields.

Tools

• Familiarity with simulation tools and data analysis software relevant to manufacturing processes.