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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI for Software Reuse and Agentic Development - **Company:** TU Delft - **Location:** Delft, Netherlands - **Salary:** €3,204.0 - €4,051.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Code Reuse, Software Debugging, Machine Learning, Software Maintenance, Software Engineering, Software Repository, Enterprise Software Applications, AI Coding Agents, Agentic-AI, Information Technology, Code Restructuring - **Published:** October 30, 2026 - **Apply:** https://www.academictransfer.com/en/jobs/365163/phd-position-in-ai-for-software-reuse-and-agentic-development/apply/ ## About the Role Required * Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field * Proficiency in the English language Additional requirements: * Research focus, characterized by curiosity, data fluency, and critical thinking * Engineering mindset, including ability to create experimental prototypes and demonstrators * Team player, good listener, and ready to help To thrive as a PhD candidate, it's crucial to have a strong research mindset driven by curiosity and passion for your topic. Reflecting on your motivation for pursuing a PhD trajectory is essential, as this path involves unique challenges and uncertainties inherent to scientific exploration. Success requires dedication, adaptability, the ability to analyze complex problems, manage your time effectively, innovate and stay resilient under pressure. Combined with the ability and willingness to work independently and collaborate well, these qualities are indispensable for a fulfilling PhD journey. These experiences will build you as an independent researcher, expand your professional network, and pave the way for diverse career pave the way for diverse career paths, inside or outside academia., Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements. ## Description How can AI agents build on existing software instead of reinventing it? Join this collaboration between TU Delft and ING to research more reliable agentic software development., Software intensive organizations rely on increasingly large and complex software ecosystems consisting of services, libraries, APIs, frameworks, documentation, and other shared engineering knowledge. Recent advances in generative AI and software engineering agents are changing how software is developed and how developers interact with these ecosystems. TU Delft is collaborating with ING to investigate how we can make enterprise software development more sustainable and reliable in this changing landscape. We will develop new techniques and tools that help developers and AI agents make better use of existing software and developer knowledge. Our research will combine AI with software repository mining, program and architecture analysis, empirical software engineering, and studies with practitioners. The research will focus on real-world software engineering challenges at ING, while contributing scientific insights and open research results that can benefit the broader software engineering community. Within this collaboration, we explore two main research directions: Direction 1: Software Reuse in Enterprise Software Ecosystems Large organizations invest substantially in reusable software assets. However, as a consequence similar functionality can be implemented independently across teams, increasing fragmentation and long-term maintenance costs. AI-assisted software development makes this challenge even more important: software engineering agents can rapidly generate new code, but may reproduce functionality that already exists elsewhere in an organization. This direction investigates how software assets are discovered, consumed, adapted, and evolved across large software ecosystems. We will study where opportunities for reuse exist, how software can successfully be adapted across teams, how reusable assets evolve over time, and how developers and AI agents can be guided towards suitable existing software. Ultimately, we aim to develop intelligent techniques that help organizations maximize reuse while reducing unnecessary duplication and maintenance effort. Direction 2: Reliable Agentic Software Development AI software engineering agents can increasingly perform tasks such as implementing features, fixing bugs, testing, and refactoring software. Their success, however, depends not only on the underlying AI models, but also on the engineering context available to them. In enterprise environments, relevant knowledge is distributed across source code, documentation, architecture descriptions, requirements, APIs, development history, and organizational practices. This direction investigates the engineering foundations required for reliable agentic software development. We will study what context agents need for different software engineering tasks, what makes specifications sufficiently complete and precise, how stale or incomplete context and software complexity affect agent performance, and how organizations can determine when tasks can be reliably delegated to AI agents. The goal is to develop techniques and safeguards that enable organizations to integrate increasingly autonomous software engineering agents while maintaining software quality and human oversight., Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.