Cifre - Phd Thesis - Root Cause Analysis and Impact Assessment with Generative Ai in Itsm
il y a 6 jours
**Company Description**
At **EASYVISTA**, we place great importance on the **well-being of all our employees**, which is why we were awarded the **Great Place To Work® certification for 2022-2023**.
Are you looking to join a **fast-growing French software company** that puts **professional development and employee success** at the heart of its strategy?
As a **market leader in ITSM**, EasyVista has recently acquired **three technology companies** specializing in ITOM, further strengthening and expanding our software offering.
Our goal is to **grow globally** and **double our revenue over the next five years**. To achieve this, we are **investing in our people**. Human values are central to our company culture, enabling our employees to thrive within **expert, multidisciplinary teams**.
Do you hold a Master 1 and have strong skills in **data science, machine learning, and statistics**?
Are you passionate about **Big Data analytics**?
Do you want to work in an **Agile environment** within an **AI Lab team**?
Are you looking for a **PhD opportunity in computer science focused on causality and LLMs**?
If you enjoy challenges and a collaborative culture, then don’t hesitate and **join us**
The core objective of this thesis is twofold:
- A benchmark comparison of existing RAG and Path-RAG approaches for RCA/IA tasks.
- An in-depth evaluation of LLMs' causal reasoning abilities in operational contexts.
- A novel methodological framework that integrates causality and graph-based retrieval into generative pipelines.
**References**:
Chen, B., Guo, Z., Yang, Z., et al. PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational Paths. 2024.
Wu, A., Kuang, K., Zhu, M., et al. Causality for Large Language Models. 2024.
**Qualifications**
- Strong command of Machine Learning concepts
- Good understanding of statistical and mathematical models
- Design and implementation of new analytical models
- Familiarity with NLP (Natural Language Processing) models
- Development of machine learning algorithms in Python
- Agile methodologies and industrialization practices: unit testing, Git, etc.
**Additional Information**
These tasks will be carried out in an **Agile environment** that has been in place for several years, with a strong focus on **team collaboration** and **close cooperation with various stakeholders** involved in the product. A **results-oriented mindset**, **initiative**, and **the ability to make proactive suggestions** will be key assets for the success of this internship.
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