Responsibilities:

1. Drive and contribute to cutting-edge research projects in NLP/ML.

2. Develop benchmarks and baselines using publicly available datasets.

3. Train large language models (LLMs) on innovative, practical tasks.

4. Publish research findings at leading NLP/ML/AI conferences and in top journals.

Requirements:

1. Currently in the PhD degree in NLP, Machine Learning, or a related area, or recently submitted the thesis; available at least three days per week (with the supervisor and university approval).

2. At least one publication in a top-tier NLP/ML conference or journal (e.g., ACL, NAACL, EMNLP, EACL, NeurIPS, ICLR, ICML).

3. Hands-on experience with Python and deep learning libraries, especially PyTorch, Hugging Face, and Transformers.

4. Experience in one or more of the following areas: supervised fine-tuning of LLMs, LLM self-learning, LLM efficiency, LLM-based AI agents, or LLM applications in gaming, reasoning, or mathematical tasks.

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