Scientific Assistant
Mission
Main duties and responsibilities
- Collaborate with other team members to help build the dataset, extracting Wikipedia articles and edit histories to enable annotation and model training.
- Develop a prototype based on LLMs to detect and classify culturally weaponized content in Wikipedia articles and their revision histories.
- Fine-tune and evaluate language models (e.g., Hugging Face Transformers) for multiclass classification tasks using the annotated dataset.
- Design and conduct experiments primarily based on transformer models (e.g., BERT).
- Document code, ensure reproducibility, and contribute to open-source dissemination of the tool.
- Work with experts in history and cultural studies to validate model results in a human-in-the-loop setup.
- Contribute to the writing of technical content for academic publications, project reports, and future research proposals.
- Participate in EPFL/UNIL research meetings and collaborate within an interdisciplinary team.
Profile
- Experience with transformer-based language models (e.g., BERT, RoBERTa, LLaMA) and fine-tuning using frameworks such as Hugging Face and PyTorch.
- Familiarity with text classification, multilingual datasets, and model evaluation.
- Strong Python programming skills and experience with version control (e.g., Git).
- Ability to write clean, reproducible, and well-documented code for research purposes.
- Interest in digital cultural heritage, or political and historical narratives, is a plus.
- Excellent command of English (spoken and written) is essential for communication within the project.
- Knowledge of Ukrainian, Armenian, or Russian is a plus, but not required.
We offer
- A stimulating interdisciplinary research environment at the intersection of AI, digital humanities, and cultural studies, within a leading technical university (EPFL) and in collaboration with UNIL.
- The opportunity to contribute to a high-impact project addressing cultural manipulation and historical narratives in digital spaces.
- Flexibility in working hours (30% part-time), with the possibility of remote or hybrid work arrangements.
- Supervision and mentoring by researchers in natural language processing, history, and digital heritage.
- The chance to co-author academic publications and contribute to open-source research outputs.
Informations
Contract Start Date :01.01.2026
Activity Rate Min : 30 %
Activity Rate Max : 30 %
Contract Type:CDD
Duration: 12 months
Contact : hamest.tamrazyan@epfl.ch