Thesis AI-Powered Knowledge Sharing for Embedded Software Team
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Job Summary
The rapid emergence of AI-powered development tools coding assistants and knowledge agents is changing the way software teams work. These tools have the potential to improve development eAiciency code quality onboarding and knowledge sharing. However it remains unclear which tools provide the most value in an industrial software development environment and how company-specific knowledge can be eAectively integrated.
Problem Statement
Software teams often rely on fragmented documentation coding guidelines and expert knowledge that may be diAicult to access or maintain. While AI tools oAer new possibilities for knowledge retrieval and development assistance their benefits limitations and integration requirements within a professional software team are not yet fully understood.
Methodology
The work will involve a market study of existing AI tools the development of evaluation criteria and the implementation of one or more proof-of-concept solutions. DiAerent approaches for providing company-specific knowledge to AI systems will be investigated such as document repositories retrieval-augmented generation (RAG) and custom AI assistants. The solutions will be evaluated based on usability accuracy maintainability security and practical value for the development team. This research aims to evaluate the applicability of AI tools and agents within the application software team. The objectives include: - Evaluating available AI development and knowledge-assistance tools - - - - Identifying benefits drawbacks and risks of diAerent solutions Investigating methods for integrating team-specific documentation coding guidelines and development practices into AI agents Exploring approaches for maintaining and sharing AI-based knowledge across the team Assessing the impact on developer productivity onboarding and software quality
Expected Outcomes
- - - - - Overview and comparison of relevant AI tools for software development teams in an industrial environment Recommendations for AI adoption within the application software team Proof-of-concept implementation of a team-specific AI assistant Guidelines for managing and sharing AI-based knowledge Assessment of benefits limitations and implementation eAort
Qualifications :
Who are we looking for
A motivated thesis student with a hands-on mindset strong problem-solving skills and an interest in industrial automation robotics and product development.
Relevant skills
Control Engineering
Software Engineering
Additional Information :
What we offer you
- A place in an enthusiastic young organisation with the necessary ambitions
- The necessary freedom and the opportunity to take initiatives
- Location Office : Lokeren
- Satellite office in Berchem ( Antwerp )
Unsolicited representations by third parties (recruitment agencies headhunters ...) of CVs via mail and/or telephone for our vacancies are considered as direct applications where no compensation is provided to the third party. Any T&Cs from these third parties will not be accepted unless upon signature of the T&Cs by a person in charge of HR. Candidates remain registered in the system for 12 months and cannot be proposed again during this period.
Remote Work :
No
Employment Type :
Full-time
About Company
The warehouse of the future is equipped with our iFollow autonomous robots instead of forklifts and our Atlas 2D pallet shuttles or eScala tote shuttles that allow for high-density storage (no wasted space!) and scalable solutions.
