Research Associate

Cardiff University; Cardiff; Hybrid; GBP 41,000 - 46,000; Full time

Benefits offered by this job

Living Wage

Hybrid work

Apprenticeship training

Job summary

Cardiff University is seeking a Research Associate to join the NLP team in the School of Computational & Mathematical Sciences. You will conduct NLP/AI research within the SYLFAEN-PSY project and develop methods for extraction and inference in mental health research.

Required are a PhD (or near completion) in a related field and strong experience in NLP, ML, Python, PyTorch, and Hugging Face. The role offers blended working, a supportive environment, and a living wage with progression

Qualifications

• PhD or nearing completion in a related subject area or relevant industrial experience.
• Expertise in Large Language Models, NLP, ML.
• Experience in medical applications is desirable.

Responsibilities

• Conduct research in NLP/AI within the SYLFAEN-PSY project.
• Develop AI methods for extraction and inference in mental health research.
• Collaborate across multidisciplinary teams and publish findings.

Skills

NLP

Machine Learning

Python

PyTorch

Hugging Face

LLMs

Education

PhD (or nearing completion)

Postgraduate degree

Tools

Python

PyTorch

Hugging Face

Job description

Job Advert

Research Associate

We are looking for a Research Associate to join theNLP team in the School of Computational & Mathematical Sciences at Cardiff University.

In this role, you will:

Conduct research within Natural Language Processing and Artificial Intelligence withinthe SYLFAEN-PSY project led by Cardiff University’s School of Medicine. The main goal will be to develop new AI methods for the extraction and inference in mental health research, delivering a solution for assessing the experiences of people with psychosis at scale.

We’d like to hear from you if you:

• Hold a postgraduatedegree at PhD level (or nearing completion / submission) in a related subject area or relevant industrial experience.
• Have expertise in Large Language Models, Natural Language Processing, Machine Learning.
• With knowledge or understanding of research outputs within medical applications (desirable).

We can offer you the chance to work in a vibrant organisation, with great benefits and opportunities for progression. We are a proud LivingWage supporter.

As part of this role, we can explore the possibility of the successful candidate accessing further training and development through an on-the-job apprenticeship. The appropriate level and type of apprenticeship training will be discussed with the successful applicant.

This role is eligible to be offered on a blended working basis, meaning that as well as spending time working on campus you may spend some time working from another location, e.g. your home. The University is committed to offering this flexibility, wherever the role and business need allows, supporting work-life balance.

Please contact Jose Camacho Collados ([e-mail]) or Victor Gutierrez Basulto ([e-mail]) for an informal, confidential discussion about the role. Or Yvonne Taylor ([e-mail]) for discussions around the school itself. This post is full-time, and fixed term for a period of 24 months.

Salary: £41,064 per annum (Grade 6), with 4 annual increments up to £46,049 per annum, at the top of the scale.

Date advert posted: Tuesday, 22 September 2026

Closing date: Wednesday, 7 October 2026

Cardiff University is committed to supporting and promoting equality and diversity and to creating an inclusive working environment. We believe this can be achieved through attracting, developing, and retaining a diverse range of staff from many different backgrounds. We therefore welcome applicants from all sections of the community regardless of sex, ethnicity, disability, sexual orientation, trans identity, relationship status, religion or belief, caring responsibilities, or age. We especially welcome and encourage applications from those under-represented groups within the University workforce, such as those who identify as LGBT+, Ethnic Minority or those with disabilities. In supporting our employees to achieve a balance between their work and their personal lives, we will also consider proposals for flexible working or job share arrangements.

Applications may be submitted in Welsh, and an application submitted in Welsh will not be treated less favourably than an application submitted in English.

Cydymaith Ymchwil

Rydym yn chwilio am Gydymaith Ymchwil i ymuno â'r tîmProsesu Iaith Naturiol yn Gwyddorau Cyfrifiadol a MathemategolCaerdydd.

Yn y rôl hon, byddwch yn:

• Dal gradd ôl-raddedig ar lefel PhD (neu fod yn agos at ei chwblhau / ei cyflwyno) mewn maes pwnccysylltiedig, neu fod â phrofiad diwydiannol perthnasol.
• Arbenigedd mewn Modelau Iaith Mawr, Prosesu IaithNaturiol, Dysgu Peirianyddol, ynghyd â thystiolaeth o allbynnau ymchwil o ansawdd uchel ac yn enwedig mewn cymwysiadau meddygol (er nad oes orheidrwydd).
• Meddu ar sgiliau rhaglennu cryf (e.e., Python, Pytorch aHugging Face), sgiliau cyfathrebu rhagorol, a'r gallu i weithio'n annibynnol acar y cyd mewn amgylchedd rhyngddisgyblaethol.

Gallwngynnig cyfle ichi weithio mewn sefydliad bywiog sy’n cynnig buddion gwych a chyfleoedd i ddatblygu yn eich gyrfa.Rydym yn falch o gefnogi’r Cyflog Byw.

Yn rhan o'r swydd hon, gallwn ystyried y posibilrwydd ohyfforddi a datblygu’r ymgeisydd llwyddiannus ymhellach drwy brentisiaeth yn ygwaith. The appropriate level and type of apprenticeship training will be discussed with the successful applicant.

Mae’r swydd hon yngymwys i’w chynnig ar sail gweithio cyfunol, sy’n golygu y cewch, yn ogystal â threulio amser yn gweithio ar y campws, dreulio rhywfaint o amser yn gweithio oleoliad arall, e.e. eich cartref. Mae’r Brifysgol wedi ymrwymo i gynnig yr hyblygrwyddhwn pan fo’r swydd ac anghenion y busnes yn caniatáu, a hynny er mwyn sicrhaucydbwysedd rhwng y gwaith a’ch bywyd personol.

Cysylltwch â Jose Camacho Collados ([e-mail]) a/neu Victor Gutierrez Basulto ([e-mail]) am drafodaeth anffurfiol a chyfrinachol am y rôl. Neu Yvonne Taylor ([e-mail]) ar gyfer trafodaethau ynghylch yr ysgol ei hun.

Swydd amser llawn yw hon, am gyfnod penodol o 24 mis, 1.0 cyfwerth ag amserllawn.

Cyflog: £41,064 y flwyddyn (Gradd 6), gyda 4 cynyddran blynyddol hyd at £46,049 y flwyddyn ar frig yradd.

Dyddiad hysbysebu: Dydd Mawrth, 22 Medi 2026

Dyddiad cau: Dydd Mercher, 7 Hydref 2026

Mae Prifysgol Caerdydd wedi ymrwymo i gefnogi a hyrwyddo cydraddoldeb ac amrywiaeth a chreu gweithle cynhwysol. Rydym o’r farn bod modd gwneud hyn drwy ddenu, datblygu a chadw ystod amrywiol o bobl o lawer o gefndiroedd gwahanol. Felly, rydym yn croesawu ceisiadau gan bobl o bob rhan o’r gymuned, beth bynnag fo’u rhyw, eu hethnigrwydd, eu hanabledd, eu cyfeiriadedd rhywiol, eu hunaniaeth draws, statws eu perthynas, eu crefydd neu eu cred, eu cyfrifoldebau gofalu neu eu hoedran. Rydym yn croesawu ac yn annog ceisiadau yn arbennig gan y rhai o grwpiau nad ydynt wedi’u cynrychioli’n ddigonol o fewn gweithlu’r Brifysgol, fel y rhai sy’n uniaethu fel LGBT+, o gefndiroedd ethnig leiafrifol neu'r rhai ag anableddau. Er mwyn helpu ein cyflogeion i sicrhau cydbwysedd rhwng eu gwaith a’u bywydau personol, byddwn hefyd yn ystyried cynigion i weithio’n hyblyg neu rannu swydd.

Caniateir i geisiadau gael eu cyflwyno yn Gymraeg, ac ni fydd cais a gyflwynir yn y Gymraeg yn cael ei drin yn llai ffafriol na chais a gyflwynir yn Saesneg.

Cardiff University is a signatory to the San Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions we will evaluate applicants on the quality of their research, not publication metrics or the identity of the journal in which the research is published. More information is available at: Responsible research assessment - Research - Cardiff University

Mae Prifysgol Caerdydd wedi llofnodi Datganiad ar Asesu Ymchwil (DORA) San Francisco, sy’n golygu y byddwn, wrth wneud penderfyniadau cyflogi a dyrchafu, yn gwerthuso ymgeiswyr ar sail safon eu hymchwil, nid ar sail metrigau cyhoeddi na’r cyfnodolyn y mae’r ymchwil wedi’i chyhoeddi ynddo. Ceir rhagor o wybodaeth yma: Asesu ymchwil yn gyfrifol - Ymchwil - Prifysgol Caerdydd