PhD – AI-driven Software Instrumentation – Austria

Job profile:

Under the guidance of the Area Management, the candidate will be deployed in the entire portfolio of application-oriented research activities within the InstrumentAI project, conducted in collaboration with industry. The position focuses on the development of AI-supported and human-in-the-loop methods for automating and optimizing software instrumentation processes. Drawing on a strong background in software engineering, data analytics, and machine learning, the candidate will support the research team in designing, implementing, and evaluating prototype solutions that identify instrumentation points and generate and extend instrumentation code and tests. Within the scope of the project, the candidate is also expected to pursue a PhD under the supervision of Univ.-Prof. Dr. Alexander Egyed and a. Univ.-Prof. Dr. Paul Grünbacher at the Johannes Kepler University Linz (JKU).

Project context:

The project InstrumentAI, conducted in collaboration with industry, addresses the growing challenge of maintaining application observability in today’s rapidly evolving software landscape. As new technologies, frameworks, and libraries emerge at an accelerating pace, each requires precise and efficient instrumentation to ensure effective performance monitoring. The goal of InstrumentAI is to develop AI-supported methods that streamline and accelerate the instrumentation process for both entirely new technologies and extensions of existing ones. The project focuses on identifying relevant instrumentation points in new or evolving technologies and generating or extending instrumentation code and corresponding tests in a partially automated process under human supervision. The expected outcome is a prototype pipeline that supports the complete instrumentation workflow, from detection and code generation to automated testing, along with AI-driven tools that demonstrate the feasibility and practical applicability of the approach in real-world software environments.