ESI is a leading research group within the Netherlands Organization for Applied Scientific Research (TNO). It contributes to societal prosperity and well-being by advancing the high-tech sector and embedded systems engineering through a multidisciplinary approach, a robust shared research program, dedicated innovation support services, and a focused competence development program.
Its primary mission is to raise high-tech and embedded system engineering from a craft to a scientifically grounded discipline.
ESI collaborates with global technology leaders on research programs that address challenges in the design, diagnostics, and maintenance of complex high-tech systems. Our research programs are tailored to address a variety of application domains, including microelectronics manufacturing, medical imaging, industrial printing solutions, and safety & security. Engineering processes in these domains are typically characterized by multidisciplinary enabling technologies that increasingly integrate intelligent solutions. Our success lies in delivering high-impact methods, techniques, and tools that accelerate innovation in engineering processes across industry and societal applications.
Job Description
In this role, you will do applied research at the intersection of software engineering, program analysis, and industrial practice. You will collaborate with partners such as ASML, Canon, Philips, and Vanderlande, following the “industry as a lab” principle: real systems, real constraints, and results that get used.
Your work focuses on technologies for software maintenance and evolution of large codebases: program comprehension, reverse engineering, refactoring, migration, and AI-assisted techniques for software comprehension and modernization. You will investigate how program-analysis techniques, models, knowledge representations, and AI-assisted methods can support engineers in understanding, modernizing, and evolving industrial software systems.
What you’ll do
- Prototype and evaluate methods and tools for program analysis and program comprehension (e.g., static analysis, parsing, lightweight modeling).
- Extract and formalize models from software artifacts (source code, build pipelines, logs, and technical documentation) to support migration and refactoring decisions.
- Prototype and evaluate engineering-assistant concepts that support software analysis, modernization, migration, or refactoring, using program-analysis, retrieval, knowledge-based, and generative-AI techniques.
- Work in multidisciplinary project teams and co-create solutions with industrial engineers; present results in workshops and project reviews.
- Contribute to research outputs, including technical reports, internal tooling, scientific publications, and conference presentations.
Tech context
You will typically work with existing industrial assets in languages like C++, C#, and Python on Windows and Linux, and you will help teams move towards more maintainable architectures, tooling, and workflows.
Functie-eisen
What you bring:
Required qualifications:
- MSc or PhD in Computer Science, Software Engineering, Programming Languages, or a related field.
- Hands-on programming skills and the ability to work with (and improve) existing codebases; experience with at least one of C++, C#, Java, or Python.
- Experience in program analysis, compilers, language engineering, reverse engineering, software modernization, or AI-assisted software engineering.
- Ability to communicate clearly with both researchers and engineers; comfortable presenting results and recommendations.
- Team mindset and ownership: you collaborate, deliver, and iterate based on feedback and project constraints.
Nice-to-haves
- Experience with compiler tooling, language workbenches, or code-query frameworks (e.g., LLVM/Clang, Roslyn, ANTLR, tree-sitter).
- Experience applying static analysis, intelligent parsing, or lightweight modeling to extract structure from source code and documentation.
- Experience building research prototypes in Python and transitioning them into maintainable internal tooling.
- Knowledge of software engineering processes in industry (CI/CD, testing strategy, architecture, system engineering).
- Experience with AI-assisted software-engineering approaches, such as retrieval-augmented generation, code and documentation analysis, evaluation of AI outputs, human-in-the-loop validation, or knowledge-graph-based context management.
Inclusiviteit en diversiteit
Uiteraard staat deze vacature open voor iedereen die zich hierin herkent. We geloven dat diverse teams van belang zijn voor ons als lerende organisatie, die voorop wil blijven lopen in de wereld van werk. Want juist verschillen tussen mensen zorgen voor groei. Van collega's, klanten, kandidaten en daarmee van Randstad Professional. Heb jij een uniek talent? We ontmoeten je graag.