可信赖LLM启用生态系统博士职位

Introduction How can we design LLM-enabled systems that people and organizations can trust? Study how trustworthiness concerns can be translated into requirements and architectural decisions, with attention to openness, automation, control and accountability.

Job Description Large Language Models are increasingly becoming part of systems in which people, organizations, software systems and AI-enabled services work together. As these systems become more open and AI is given more responsibility, new questions arise. Who needs to trust whom, or what? What are they trusting them to do? Under what conditions are they willing to do so? And what does this mean for the requirements and architecture of these systems?

Many existing frameworks describe what trustworthy AI should provide, for example transparency, accountability, privacy, reliability, security and human oversight. The challenge is to translate these concerns into concrete requirements and architectural decisions. These concerns can also conflict. More transparency may affect privacy, for example, while more automation may reduce human control.

In this PhD, you will work at the intersection of requirements engineering, software architecture and trustworthy AI. You will study how different stakeholders understand trust in LLM-enabled systems and how their expectations, together with organizational and regulatory concerns, can be translated into requirements and architectural drivers. You will also study how different stakeholders can reason about choices concerning openness, information sharing, automation, human oversight and accountability.

You will develop and evaluate methods and models that help architects and other stakeholders identify trustworthiness requirements and make informed architectural decisions. Possible outcomes include approaches for eliciting and analyzing trust requirements, architecture principles or patterns, and contributions to a reference architecture. The exact direction and artefacts will develop during the PhD, giving you room to shape your own research questions and contributions. This PhD is part of LLM4LM (Large Language Models for Logistic Management), a collaborative research project involving TU/e, TNO and several industry partners. The project investigates how LLMs and related AI technologies can support logistics and regulatory compliance in reliable, transparent and trustworthy ways. You will have the opportunity to study real AI adoption and architectural decision-making as it unfolds, working with academic and industry partners and across different application cases. The research will use an empirical and design-oriented approach. Depending on the research questions, this can include interviews, workshops, document analysis, case studies, and the design and evaluation of methods or models. You will build on and contribute to ongoing research within LLM4LM while developing your own PhD research trajectory.

Job Requirements • A master’s degree (or an equivalent university degree) in Computer Science, Software Engineering, Information Systems, Industrial Engineering, or a related field. • A research-oriented attitude and an interest in requirements engineering, software architecture, or software design and decision-making. • An interest in trustworthy AI and LLM-enabled systems. Prior experience in LLM development is welcome but not required. • An interest in empirical research and working with people and organizations. • Ability to think conceptually and critically about complex socio-technical problems and translate them into research questions. • Ability to work in an interdisciplinary team and interest in collaborating with industrial partners. • Motivated to develop your teaching skills and coach students. • Your communication skills are excellent as is your proficiency in English and your ability to collaborate in an international setting.

Conditions of Employment A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station.

In addition, we offer you: • Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities , scale P (min. € 3,204 - max. € 4,051 gross base salary per month (full-time)). • In addition to your base salary, you will receive an 8% holiday allowance and an 8.3% year-end bonus, both calculated based on your annual gross base salary. • Generous leave options: a standard 29 days (based on a 38 hour working week) per year that you can increase to 41 days by working two hours more per week (flexible working hours). This is prorated if you work part-time. • As a TU/e employee, you participate in the ABP pension scheme, providing retirement pension and pension benefits for surviving dependents and occupational disability. TU/e pays 70% of the pension premium, while employees contribute the remaining 30%. • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . • An excellent technical infrastructure, and on-campus children's day care. • Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate. • We support your wellbeing with free 24/7 access to OpenUp, providing you and your family with mental health support, expert guidance, and online training. • An allowance for commuting, working from home and internet costs. • A Staff Immigration Team and a tax compensation scheme (the Expat Scheme ) for international candidates.

On our website you can discover even more information about our conditions of employment . Build on your career at TU/e!

About us We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community. Our university is located in Brainport Eindhoven — a world‑leading tech region with more than 7,000 high‑tech companies and strong R&D activity. Known for breakthroughs in AI, photonics, semiconductors and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here . The Industrial Engineering & Innovation Sciences (IE&IS) department combines disciplinary knowledge from the humanities, social sciences and technical sciences to solve the complex problems of industries and society. We collaboratively focus on and create responsible and effective innovations for the research themes: Humans and Technology, Supply Chain Management, Sustainability and Circularity, and Value of Data-Driven Intelligence.

Information Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Maryam Razavian ( m.razavian@tue.nl ). Visit our website for more information about the application process . You can also contact HRServices.IEIS@tue.nl. Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video . Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application We invite you to submit a complete application by using the apply button. The application should include a: • Cover letter in which you describe your motivation and qualifications for the position. • Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application. • Brief description of your MSc thesis (topic, method, contribution) and other related research projects that you conducted. • List of Master's and Bachelor’s courses, including grades.

Ensure that you submit all the requested application documents. We give priority to complete applications.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

Please note • You can apply online. We will not process applications sent by email and/or post. • A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines . • Please do not contact us for unsolicited services.