PhD Candidate in Machine Learning-based Code Analysis

The successful candidate will join the Serval research group by working on the MiCE (FNR-funded) project. The subject of the thesis will be “Assessing and Improving ML-based Code Analysis techniques” with supervisor Dr. Mike Papadakis. Successful PhD candidates will extensively explore and develop software engineering techniques that include the feasibility, practicality and success evaluation of prototype implementations.

The team you will be working with Mike Papadakis.

The position holder will be required to perform the following tasks/will do research on the following topics:

• Forming learning-based code analysis techniques combining pre-trained models and user defined features.
• Forming generic embeddings, combining both static and dynamic features, that can improve the performance of learning-based code analysis techniques.

PhD Student Role: Under the direction of a professor, the candidate will carry out research activities and write a thesis with the main goal of obtain a PhD in the area of Software Engineering. This includes conducting literature surveys and establishing state-of-the-art; developing necessary experimental and simulation facilities where required; planning, executing, and analyzing experiments and simulations; conducting joint and independent research activities; contributing to project deliverables, milestones, demonstrations, and meetings; disseminating results at international scientific conferences/workshops and peer reviewed scientific publications.