Technician for adapting language models (LLMs) to sign language. (Ref. 30267230018)

Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH; España; Presencial; EUR 16.000 - 21.000; A tiempo parcial

Descripción de la vacante

Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH seeks a researcher to adapt language models to sign language, covering data prep through model training. The role focuses on data generation and model development in a collaborative research environment in Spain.

The candidate should have background in deep learning, NLP, and software development, with experience in Python, PyTorch, and Hugging Face. Part-time, temporary position with 20 hours per week starting 1 Nov 2026.

Formación

• Knowledge of Catalan Sign Language at a basic level.
• Proficiency in Natural Language Processing.

Responsabilidades

• Generate synthetic data from textual or video data.
• Develop data augmentation methods for sign language.
• Integrate computer vision and language processing for sign language.
• Adapt LLMs for understanding, translating, and generating sign language.
• Develop a prototype translation system for the medical field.
• Master Transformer architecture and adaptations to LLMs (PyTorch, Hugging Face).
• Perform NLP tasks including tokenization and embeddings.
• Evaluate text generation models.
• Program in Python with PyTorch and Hugging Face tools.
• Work with Linux-based systems.

Conocimientos

Deep Learning

Data Science

Python

NLP

Educación

Academic degree in a relevant field

Herramientas

PyTorch

Hugging Face

Descripción del empleo

Organisation/Company Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH Research Field Engineering » Communication engineering Engineering » Computer engineering Mathematics Researcher Profile First Stage Researcher (R1) Positions Research Support Positions Application Deadline 5 Oct 2026 - 23:00 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Part-time Hours Per Week 20 Offer Starting Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Reference Number 30267230018 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Mission:

Adapt language models (LLMs) to sign language, from data preparation to model training.

Functions to be developed:

• Generate synthetic data from textual or video data.
• Develop data augmentation methods for sign language.
• Integrate Computer Vision and Language Processing methods for sign language.
• Adapt LLMs for the understanding, translation and generation of sign language.
• Develop a prototype translation system for the medical field.
• Mastery of the Transformer architecture and adaptations to LLM: Deep Learning with PyTorch and the Hugging Face environment (transformers, datasets, peft, accelerate, evaluate).
• Natural Language Processing: Tokenization, embeddings.
• Evaluation of text generation models.
• Programming in Python and Pytorch and Hugging Face environments.
• Linux-based systems.

Specific Requirements

Knowledge:

• Catalan Sign Language (basic level).
• Natural Language Processing.

Professional Experience:

• Have worked on projects in Deep Learning.
• Have worked with data science or have developed software.
• Experience in functions similar to those described will be valued, specifically in the development of research activities, both in the university and industrial environment.

Languages CATALAN Level Good

Languages ENGLISH Level Good

Languages SPANISH Level Good

Research Field Engineering » Communication engineeringEngineering » Computer engineeringMathematics Years of Research Experience 1 - 4

Additional Information

€33,876.08 gross per year (full-time)

Eligibility criteria

All the candidates who cannot prove the required academic degree will be immediately withdrawn from the selection process.

The CVs will be assessed according the following general criteria:

• The maximum score for the candidates who accomplish all the eligibility criteria stated in the job offer will be 10 points.
• Threshold: 5 points.
• The maximum score (10 points) will be distributed as follows:
• 1 point for required speciality.
• 2 points for required academic training.
• 2 points for technic competences.
• 1 point for organisational competences.
• 3 points for professional experience.
• 1 point for any aspect of the candidate’s professional profile to be determined as specially relevant by the Selection committee.

If the selection committee decide to include a personal interview as additional step of the selection process, only the candidates scored 5 or above for their CV will be retained for the interview step.

The interview will be assessed according the following criteria:

• Threshold: 3 points.
• The maximum score will be distributed according the following criteria:
• 2 points for adequacy to functional competences of the job.
• 2 points for adequacy of professional experience.
• 1 point for any aspect of the candidate’s professional profile to be determined as especially relevant by the Selection committee.

The eligible candidates will be ranked from highest to lowest score, being this the selection criteria.

Selection process

The planned selection process is as follows:

• The members of the selection committee will decide for each case what the selection process will be, if an assessment is made only for the curriculum vitae or any other procedure is planned: interview, tests, etc ...
• Each phase of the selection process will be reported on the website where the offer is published. If applicable, indicate your request.
• Finally, the name of the person selected will be published on the same website where the offer is published.

Additional comments

Remember that the resume should not include any personal data or photographs.