Researcher in Natural Language Processing
- Donostia / San Sebastián
- Bilbao
Investigador/a en Procesamiento de Lenguaje Natural
We are looking for a researcher with expertise in Natural Language Processing (NLP), and at the same time motivated by the transfer of this knowledge to companies and institutions through advanced research prototypes developed to solve real needs.
The successful candidate will be part of the Department of Speech and Natural Language Technologies, participating in research projects at regional, national and European level and developing and applying technology for information retrieval, named entity detection, text classification, question-answering systems, automatic summarization and natural language understanding, mainly.
Candidates must have:
- Master's degree in Natural Language Processing or equivalent.
- Good programming skills in Python.
- Knowledge of Machine Learning, Deep Learning and Data Analytics.
- Experience in using PLN technologies in real use cases.
- Good spoken and written level of Spanish and English
- Motivation to acquire knowledge and new technical skills on an ongoing basis
- Interest in scientific research
- Proactive attitude and ability to work as a team player
We value candidates:
- PhD in the field of PLN or similar.
- Scientific articles published in conferences and/or journals in the field.
- Knowledge of generative AI with large language models or LLMs
- Experience with Machine Learning tools (Numpy, Scipy, ...) and NLP (Spacy, Fastext, Flair, ...)
- Knowledge and experience in Deep Learning environments (Pytorch, Tensorflow, Transformers and Hugging face).
- Linux development environments, GIT, Docker and web environments (Restful APIs, ...)
We offer:
- PhD in the field of PLN or similar.
- Scientific articles published in conferences and/or journals in the field.
- Knowledge of generative AI with large language models or LLMs
- Experience with Machine Learning tools (Numpy, Scipy, ...) and NLP (Spacy, Fastext, Flair, ...)
- Knowledge and experience in Deep Learning environments (Pytorch, Tensorflow, Transformers and Hugging face).
- Linux development environments, GIT, Docker and web environments (Restful APIs, ...)
