PhD position for NWO project ECHoFAIR: empowering collaborative human-AI teaming for failure analysis and intelligent risk a...

Are you passionate about improving the design and development of complex high-tech systems through intelligent tools and collaboration? We offer a challenging PhD position in the Systems Engineering and Multidisciplinary Design (SEMD) group at the Department of Design, Production and Management.

Failure Analysis and Risk Assessment (FARA) play a critical role in ensuring the reliability, safety, and performance of complex systems. However, current industrial practices, such as Failure Modes and Effects Analysis (FMEA), are time-consuming, rely heavily on scarce expert knowledge, and struggle to cope with uncertainty, large data volumes, and increasing system complexity.

At the same time, recent advances in Artificial Intelligence (AI) offer opportunities to support engineers in failure analysis, risk assessment and decision-making. Yet, these technologies are not yet sufficiently reliable, integrated, or tailored for safety-critical engineering applications.

This project aims to bridge the gap between traditional engineering practices and AI-driven methods by developing human-AI collaborative approaches for failure analysis and risk assessment.

You will investigate current FARA practices at leading high-tech companies and identify limitations in existing workflows, tools, and knowledge management. Building on this, you will contribute to the design of an integrated, AI-supported FARA process and toolchain, enabling more efficient, consistent, and scalable risk analysis across system lifecycles.

Your research will focus on enabling effective collaboration between human experts and AI systems. This includes developing methods to capture and structure tacit engineering knowledge, designing explainable AI support for risk assessment, and improving how engineers interact with intelligent tools during analysis and decision-making.

Ultimately, you will contribute to the development of a collaborative platform and methodology that combines human expertise with AI capabilities to:

• Improve the identification and understanding of failures and risks
• Enhance communication and collaboration across multidisciplinary teams
• Enable reuse of knowledge across projects and organizations
• Reduce time and effort in risk analysis while improving quality and robustness.

You will work closely with industrial partners in the Dutch high-tech sector and collaborate with researchers in systems engineering, AI, and data science. The position offers a unique opportunity to contribute to next-generation engineering practices at the intersection of Systems Engineering and Artificial Intelligence.

Requirements

Examples that are often used in PhD vacancies:

• You are an enthusiastic and highly motivated person, with an ambition to become a researcher.
• You have a creative mindset and excellent (oral, written, and technical) communication skills.
• You have a good team spirit and like to work in an interdisciplinary and internationally oriented environment.
• You are proficient in English and preferably also in Dutch.
• You are a fast learner. Some industrial experience would be considered as an appreciable bonus.
• You are able to think visually.
• You have an affinity with model driven/model based systems thinking and engineering.
• You have a background in Industrial Design Engineering, Industrial and/or Systems Engineering, Computer Science/Engineering, Embedded Systems, or equivalent engineering disciplines related to complex systems design and development.

Contract terms

• A full-time position for four years, with a qualifier in the first year, and the flexibility to work (partially) from home.
• Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU).
• You will receive a gross monthly salary ranging from €3.059,- (first year) to €3.881,- (fourth year).
• There are excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme.
• A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
• Free access to sports facilities on campus.
• A family-friendly institution that offers parental leave (both paid and unpaid).
• You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision.