Engineering Doctorate in Digital Textile Manufacturing and Systems
Develop AI-driven textile production systems to enhance circularity and scalability for SMEs through hands-on engineering and data science.
Best for:Best for engineers with a design-oriented mindset, strong hands-on technical skills, and experience in data science or machine learning who are passionate about sustainable manufacturing and interdisciplinary collaboration.
Overview
This Engineering Doctorate (EngD) position at Eindhoven University of Technology focuses on transforming traditional textile manufacturing into a digital, circular, and AI-driven process. The successful candidate will collaborate with SMEs, machine builders, and researchers to design and implement sensor-enabled textile machines, leveraging data science, machine learning, and AI to extract actionable insights. The role emphasizes hands-on experimentation, interdisciplinary collaboration, and real-world impact, aiming to optimize production workflows, reduce waste, and support sustainable practices. The project is part of a public-private fieldlab, offering mentorship and opportunities for professional growth in a dynamic, international research environment.
What you'll do
- Design and build experimental textile machine setups by integrating sensors, controls, and data connectivity to enable AI-driven production monitoring.
- Apply data science, machine learning, and AI techniques to analyze production and ecosystem data, extracting insights for operators, designers, and partners.
- Collaborate with textile producers, machine builders, and SMEs to co-design workflows, demonstrators, and open knowledge-sharing platforms.
- Analyze the broader impact of data-enabled production on the textile value chain, including design, material choices, small-batch production, repair, reuse, and recycling.
- Work within a public-private fieldlab environment, combining academic supervision with real-world industry challenges.
- Develop and implement solutions that support Dutch textile SMEs in meeting European circularity regulations while preserving craftsmanship.
Requirements
Degree required: Master’s degree (or equivalent) in Industrial Design or a related engineering field
Degree offered: Engineering Doctorate (EngD)
Language: Fluent spoken and written English
Instruction: English
- Proven hands-on experience in designing and building experimental machine setups
- Strong background in data science, machine learning, or AI applications
- Familiarity with sensor integration and data connectivity in industrial systems
- Collaborative mindset with experience working in interdisciplinary teams
- Technical proficiency in analyzing and interpreting production data
- No specific nationality or residency restrictions mentioned
- No age or prior experience caps specified
Funding & terms
How to apply
Deadline: 2026-10-16 · open until filled
Submit a complete application online through the university’s portal. The application must include a cover letter detailing your motivation and qualifications, a CV with publications and three references, copies of BSc and MSc diplomas and transcripts, and proof of English proficiency (e.g., IELTS or TOEFL results). Ensure all documents are submitted as incomplete applications may be rejected.
- Cover letter
- Curriculum Vitae (CV) with publications and three references
- Copies of BSc and MSc diplomas and grade transcripts
- English proficiency test results (IELTS or TOEFL)
Contact
Troy Nachtigall· Hiring Manager
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