37.3392, Jobs: Computational Linguistics, Morphology, Typology: Research Fellow in Computational Linguistics, University of Surrey

[The LINGUIST List]

LINGUIST List: Vol-37-3392. Mon Oct 19 2026. ISSN: 1069 - 4875.

Subject: 37.3392, Jobs: Computational Linguistics, Morphology, Typology: Research Fellow in Computational Linguistics, University of Surrey

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Date: 16-Oct-2026
From: Sacha Beniamine [s.beniamine at surrey.ac.uk]
Subject: Computational Linguistics, Morphology, Typology: Research Fellow in Computational Linguistics, University of Surrey


Job Location: Surrey, United Kingdom
Web Address: https://www.smg.surrey.ac.uk/
Job Title: Research Fellow in Computational Linguistics
Job Rank: Post Doc
Salary: £38,448 to £41,885 per annum

Minimum Education: PhD

Specialty Areas: Computational Linguistics; Morphology; Typology

Description:
We are seeking qualified applicants for a 2 year position (with
possibility to extend to 4) as Research Fellow (postdoc) in
Computational Linguistics on the UKRI FLF grant ‘Scaling
predictability in Morphological paradigms’, led by Sacha Beniamine.
The successful candidate will perform a key role in creating new
software tools and employing them to measure predictability in
morphology. The position is based at the Surrey Morphology Group at
the University of Surrey, in Guildford, and provides the opportunity
to work in the vibrant and highly collegial research environment for
which the SMG is renowned.
The successful candidate will be in charge of the Work Package
focusing on New Models, which aims to enable precise and comparable
measures of morphological predictability, in order to understand how
predictability is organized in realistic, complex inflectional
systems.
As a core member of the team, the successful candidate will use their
skills in software development to extend existing software (Qumin)
which analyzes morphological lexical data and evaluates inflectional
predictability. They will rely on their qualifications in linguistics
to study predictability in systems which challenge existing tools and
analyses, pushing the edge of what can be reliably measured and
contribute to the large comparative study of macro-variation in
predictability, gaining experience in linguistic typology. They will
collaborate closely with the team in the writing and dissemination of
papers and presentations, and be expected to take initiative in the
formulation of the research agenda.
About You:
The successful candidate will have a dual background in linguistics
and software development, with a PhD in computational linguistics,
natural language processing, or a related field. The candidate will
have a good grasp of linguistic concepts and methods. They will have
an interest in the inflectional morphology of at least one language or
language family, which can serve as a test-bed for the tools they will
develop. They will have experience of software development, and are
fluent in Python programming. Candidates with experience programming
as part of a team will be preferred.  Mastery over software
development tools (command line; git management; continuous pipelines
and workflows; IDE) is essential. An interest in reproducibility in
science will be an advantage. Experience in using these skills to
answer linguistic questions is essential.
Further Details:
Interviews are planned for Tuesday the 24th of November and will be
held online. Please contact Sacha Beniamine, s.beniamine at surrey.ac.uk
with any questions.

Application Deadline: 30-Oct-2026
Mailing Address for Applications:
        United Kingdom
Web Address for Applications:
https://jobs.surrey.ac.uk/Vacancy.aspx?id=15849&forced=2
Application Instructions:
Please submit your application online at
https://jobs.surrey.ac.uk/Logon/?jobId=15849
Applications require:
    - CV
    - Contact details for 2 academic referees.
    - Three relevant works of research (DOI/URL links if possible).
    - Research statement of one page, describing research interests
and experience, and how you think this makes you suitable for the
advertised post (Please do not seek assistance from AI tools in
writing this document).
Contact Information:
        Sacha Beniamine
        Email: s.beniamine at surrey.ac.uk



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