Research assistant in natural language processing for accessible science

University of Surrey
Guildford
1 month ago
Applications closed

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About the Project

The Centre for Translation Studies (CTS) is dedicated to cutting‑edge research, scholarship and teaching in translation, and related modalities of intra‑lingual, cross‑lingual and cross‑modal communication, including modalities aimed at enhancing accessible communication. Since its foundation in 1982, CTS has contributed to the theoretical advancement of translation and interpreting studies, whilst achieving real‑world applicability by studying translation and interpreting as socio‑technological practices, highlighting their economic and social value and their role as an enabling force for a globally connected world. The CTS at the University of Surrey is seeking a research assistant in natural language processing for accessible science to contribute to the Terminology‑Aware Machine Translation for Accessible Science (TaMTAS) project, funded by EPSRC under the CHIST‑ERA Call 2025: Science in Your Own Language. Bridging machine translation, natural language processing and scientific expertise, this project addresses the urgent need for accurate and accessible scientific communication by enabling multilingual access to scientific knowledge. It challenges the dominance of English in scientific dissemination and aims to empower researchers and the general public to engage with science in their native languages. The project brings together an outstanding international consortium, including collaborators from Universitat Oberta de Catalunya, Barcelona Supercomputing Center, Dublin City University and the University of Tartu.


Position Overview

We are seeking a Graduate Researcher with a background in natural language processing, computational linguistics or a related discipline to join the multidisciplinary team working on the project. The successful candidate will focus primarily on WP4—Terminology‑aware Quality Estimation and Automatic Post‑Editing (APE)—developing models capable of identifying and characterising terminological errors, their span and severity, with a focus on critical domain errors. They will also contribute to WP5—Text Augmentation—enhancing scientific content for accessibility and educational reuse. The role requires collaboration with project partners, preparation and presentation of research results, and good communication skills.


Responsibilities

  • Contribute to WP4 (Terminology‑aware Quality Estimation and Automatic Post‑Editing) by developing models to identify and characterise terminological errors.
  • Contribute to WP5 (Text Augmentation) by enhancing scientific content for accessibility and educational reuse.
  • Collaborate with partners across the consortium; co‑author and present research findings.
  • Maintain effective communication with project stakeholders.

Qualifications

  • Graduate level training in natural language processing, computational linguistics or a related field.
  • Experience with machine translation, text accessibility and large language models (LLMs) for evaluation.
  • Strong programming skills.
  • Familiarity with LLMs for quality estimation such as the GEMBA prompt is desirable.
  • Knowledge of any of the consortium languages in addition to English (Spanish, Catalan, Estonian or Irish) is a bonus.

Position Details

  • Part‑time role for 2 years with possibility of extension until 31 Jan 2029.

Benefits

  • Generous pension scheme.
  • Relocation assistance where appropriate.
  • Flexible working options including job share and blended home/campus arrangements.
  • Access to world‑class leisure facilities on campus.
  • Range of travel schemes.
  • Family‑friendly benefits including an excellent on‑site nursery.

About the University

The University of Surrey is a global university with a world‑class research profile and an enterprising and forward‑thinking spirit, committed to research and innovation excellence and to benefitting the economy, society and the environment. Its researchers practise excellence against a backdrop of technological, human, health and social sciences, and their strong linkages forged in an integrated campus culture of cooperation.


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