Computational Intelligence Lab, Postdoctoral Fellow

The Computational Intelligence Lab targets NLP, Time Series Forecasting/Generation, Knowledge Processing using Deep Learning. Applications are expected to construct high-level information extraction systems by conducting full fine tuning, fine tuning, LoRA tuning w.r.t. material knowledge against LLMs. Research results should be disseminated to international conferences and journal papers. This is project-based position.

Work content and job description
Studies on materials informatics. Knowledge on Pytorch, Transformer, Mamba are required. Good experience on model fine-tuning and Low Rank Adaptation is essential.

Various systems
Transportation expenses :
Housing allowance or Transportation expenses depending on conditions

Insurance
Employees' Health Insurance :
Private School Mutual Aid

Measures for preventing passive smoking at the workplace
No smoking on the campus. Smoking area is located outside the campus.

Considerations for conducting interviews (e.g., those who live far away, such as overseas)
For residents in Japan, travel expenses for the interview will be provided. Residents living abroad will be interviewed online.

Job content supplemental explanation
Reseach on introducting material science knowledge into deep learning models such as Large Language Models (LLMs). More concretely, our project include introducing material science knowledge into knowledge graphs and conducting representation learning on the graphLLMs, then introducing meterial science knowledge into large langauge models. Background knowledge in material science will be an asset. Skills on the fine tuning of large language models and knowledge representations of knowledge graphs under the Pytorch environment are expected. Target data are written in English.

Notification of result
Candidates on a short list will be contacted via email. The result will be notified by e-mail.