Applied Researcher – Software Engineering & AI

Randstad - Netherlands; Eindhoven; On-site; EUR 65,000 - 90,000; Full time

Job summary

TNO ESI is a leading research group within the Netherlands Organization for Applied Scientific Research (TNO). It advances embedded systems engineering and high-tech research through multidisciplinary programs and industry partnerships.

The role focuses on software maintenance, program analysis, and AI-assisted methods for evolving large codebases. You will collaborate with industry partners, prototype new analysis tools, and contribute to publications and internal tooling.

Qualifications

• MSc or PhD in Computer Science, Software Engineering, Programming Languages, or a related field.
• Hands-on programming skills 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 researchers and engineers; comfortable presenting results and recommendations.
• Team mindset and ownership: collaborate, deliver, and iterate based on feedback and project constraints.

Responsibilities

• Prototype and evaluate methods and tools for program analysis and program comprehension (static analysis, parsing, modeling).
• Extract and formalize models from software artifacts to support migration and refactoring decisions.
• Prototype and evaluate engineering-assistant concepts 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 reviews.
• Contribute to research outputs, including technical reports, internal tooling, scientific publications, and conference presentations.

Skills

C/C++/C#/Java/Python

Program analysis

Reverse engineering

AI-assisted software engineering

Communication

Education

MSc or PhD in Computer Science / Software Engineering

Tools

LLVM/Clang

Roslyn

ANTLR

tree-sitter

Job description

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 andembedded systems engineering through a multidisciplinary approach, a robust shared researchprogram, 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 ascientifically grounded discipline.

ESI collaborates with global technology leaders on research programs that address challenges in thedesign, diagnostics, and maintenance of complex high-tech systems. Our research programs aretailored to address a variety of application domains, including microelectronics manufacturing,medical imaging, industrial printing solutions, and safety & security. Engineering processes in thesedomains are typically characterized by multidisciplinary enabling technologies that increasinglyintegrate intelligent solutions. Our success lies in delivering high-impact methods, techniques, andtools 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.