Research EngineerApplications Closed

Martin Krallinger, Dr.

Unknown Organization
Barcelona Supercomputing Center (BSC-CNS)
Apply by Sep 26, 2025

Application deadline

Sep 26, 2025

Job

Job location

Martin Krallinger, Dr.

Geocoding

Barcelona Supercomputing Center (BSC-CNS)

Geocoding in progress.

Source: legacy

Quick Information

Application Deadline

Sep 26, 2025

Start Date

Flexible

Education Required

See description

Experience Level

Not specified

Job

Job location

Martin Krallinger, Dr.

Geocoding

Barcelona Supercomputing Center (BSC-CNS)

Geocoding in progress.

Source: legacy

Map

Job Description

The Natural Language Processing for Biomedical Information Analysis (NLP4BIA) group at BSC is an internationally renowned research group working on the development of NLP, language technology, and text mining solutions applied primarily to biomedical and clinical data. It is a highly interdisciplinary team, funded through competitive European and National projects requiring the implementation of natural language processing and advanced AI solutions making use of diverse technologies, including Transformers and recent advances in Large Language Models (LLM) to improve healthcare data analysis. The NLP4BIA-BSC is looking for a Research Engineer with experience in Language Technologies and Deep Learning. The candidate will be involved in technical work related to international projects, being part of a team of researchers working on topics related to clinical Language Models, multilingual NLP, benchmarking of language technology solutions and predictive content mining. The candidate will have the opportunity to advance the state of the art of biomedical language models and NLP methods working in a multidisciplinary environment alongside AI experts, computational linguists, clinical experts, and other engineers.

Requirements

  • University degree in Computer Science
  • Computational Linguistic
  • or engineering discipline. Candidates with a minimum of a master's degree will be considered. Demonstrated experience in Natural Language Processing technologies. Experience in developing and training models using transformer architectures. Practical experience with deep learning libraries (e.g. Pytorch
  • TensorFlow
  • Spacy
  • Transformers…). Knowledge of deep learning methods for pre-training large language models using transformer architectures (like BERT
  • RoBERTA
  • DeBERTA
  • GPT
  • Bloom) as well as learning to implement LLMs. Advanced programming skills in Python. Experience in software development resources (Git).

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