Doctoral Candidate (PhD) in Computer Science / Information Systems Engineering on Large Language Models (LLMs)
The successful candidate will join the young, vibrant, and interdisciplinary FINATRAX Research Group, which builds bridges between business research and information systems engineering. The group conducts research on the application and the impact of emerging technologies like DLT/Blockchain, GenAI, Natural Language Processing, Machine Learning, Human-Computer Interaction, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds (e.g., policy, business, technology), united in pursuit of sustainable technologies that positively impact society. For more information, please visit our website: https://wwwen.uni.lu/snt/research/finatrax/projects
The successful candidate will pursue a Ph.D. degree (Doctorate) in computer science / information systems engineering. In this project, the aim is to bridge the gap between large language models (LLMs) and task automation, enabling natural language interaction, that is, via a chatbot, to access and control automation tools safely. In particular, architectures enabling the communication between LLMs and task automation tools as well as corresponding security and business implications will be investigated.
In general, the candidate will perform the following tasks:
- Carry out research in fields of interest to the research group, such as:
- Deploying and benchmarking state-of-the-art LLMs with respect to cost, performance, and data protection
- Developing and deploying LLM based architectures for task automation
- Investigating the performance of hybrid LLMs – knowledge-based approaches for task automation
- Using Design Science Research (DSR) methodology, collaborate with our industry partner to gather requirements for task automation, evaluating the potential of hybrid LLMs to effectively address these needs and optimize workflows.
- Investigation of state-of-the-art methods from explainable AI and adaptation of suitable methods for task automation
- Disseminate results through scientific publications in outlets on the intersection between information systems and computer science
- Support the conceptualization and writing of research proposals to attract industry partnerships as well as national and European grant projects
- Conduct research projects and create project deliverables
For further information, please contact, Igor Tchappi (igor.tchappi@uni.lu ) or Gilbert Fridgen (gilbert.fridgen@uni.lu ).
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