HYBRIDS Doctoral Fellow

University of London


Department: School of Electronic Engineering & Computer Science
Salary: £45,174.92 per annum (inclusive of mobility fee and family allowance, where applicable).
Reference: 00dc11
Location: Mile End
Date posted: 14 March 2023
Closing date: 26 April 2023

Cross-lingual claim detection for fact-checking
Reference number: HYBRIDS- DC11
PhD research topic: Cross-lingual claim detection for fact-checking
Host institution: Queen Mary University of London , United Kingdom
PhD Enrolment: Queen Mary University of London, United Kingdom
Main Supervisor: Dr Arkaitz Zubiaga (http://www.zubiaga.org/),  Queen Mary University of London, [email protected]
Co-supervisor: Dr Rubén Miguez, Newtral Media Audiovisual (NEWTRAL)
Inter-sectoral Supervisors: Ms. Vindhya Singh and Ms. Stephanie Öttl, Industrieanlagen- Betriebsgesellschaft (IABG)
(1) To design a strategy to detect potentially verifiable sentences, also known as claims; this is the first task before producing an informed assessment of the veracity of the claim, known as fact-checking;
(2) To define annotation criteria for claim detection and collect a multilingual dataset of claims annotated with those criteria within the political domain;
(3) To use cross-lingual methods to deal with multilingual data;
(4) To cluster together related claims, including potential contradictions, which further informs the fact-d
Expected outcomes:
(1) Development of a cross-lingual system aimed at detecting and clustering multilingual claims, as a first step both to assist fact-checkers in the selection process and to feed an automated fact-checking system.
(2) Elaboration of a multilingual dataset of political claims labelled according to the criteria considered in the previous analysis.
(3) Use cases on climate emergency and health.
Planned secondments:
Hosting Partner
No. of months
Expected date
Training in fact checking methodologies and developing use cases on climate emergency, immigration, and Euroscepticism.
Newtral Media Audiovisual (NEWTRAL)
Evaluation of the systems developed.
Newtral Media Audiovisual (NEWTRAL)
Gaining experience in the development of end-user tools aimed at fact checking of health information.
Industrieanlagen- Betriebsgesellschaft (IABG)
Eligibility Criteria:

  • Mobility: At the time of recruitment, the researcher must not have resided or carried out his/her main activity (work, studies, etc.) in United Kingdom for more than 12 months in the 36 months immediately before the recruitment date. Time spent as part of a procedure for obtaining refugee status under the Geneva Convention or compulsory national service are not taken into account.
  • The candidate must be at the date of recruitment a doctoral candidate (i.e. not already in possession of doctoral degree). Researchers who have successfully defended their doctoral thesis but who have not yet formally been awarded the doctoral degree will not be considered eligible.
  • The candidate must be working exclusively for the action.

Specific requirements:

  • Degree: All applicants should have a first-class honour degree or equivalent, or a MSc degree, in Computer Science (or a related discipline).
  • Programming skills: Excellent programming skills, ideally in python.
  • Language: Excellent command of English, together with good academic writing and presentation skills. The candidate must meet Queen Mary’s English language requirements: typically an Academic IELTS certificate with a minimum 6.5 overall score, and a minimum of 6.0 in writing and a minimum of 5.5 in reading, speaking and listening. For alternatives to IELTS, see: https://www.qmul.ac.uk/international-students/englishlanguagerequirements/postgraduateresearch/
    There are certain circumstances where you may not be required to have an  English Language test to prove your proficiency.  If you hold a degree  from a majority English speaking country or your degree has been taught  and examined in English, please read: https://www.qmul.ac.uk/international-students/englishlanguagerequirements/postgraduatetaught/#d.en.622499

Desirable skills: Excellent knowledge of data science methods, experience with deep learning methods and working with large datasets. Experience in natural language processing is also a plus.
Estimated starting date: 1st July 2023 (or as soon as possible thereafter)
Contract: Full-time contract
Duration: 36 months, including 4 secondments of 2/3 months each, at other consortium members’ premises (see Secondment section)
Salary: £45,174.92 / year (inclusive of mobility fee and family allowance, where applicable).
To view the job profile, click here
Application Documents:

  • Europass CV (template available in the following link ), including the names and contact details of two academic references, in English, highlighting the merits that are established as evaluation criteria;
  • Scans of Bachelor’s and Master’s transcripts, with certified translation in English (if the degree qualification is not in English);  If you have not yet completed your master’s, you must submit a provisional academic transcript.
  • A motivation letter in English, highlighting the consistency between the candidate profile and the chosen DC position/s for which she/he is applying and describing why you wishes to be an HYBRIDS DC to carry out a PhD; (max. 700 words)
  • Scanned copy of your ID card, resident’s card or passport currently in force;
  • Proof of excellent command of English, typically an IELTS certificate, but others are also accepted (see above).. This is not required in case of native English speakers (i.e., English is your mother tongue).

In addition, you can add any other documents which you find relevant for the applications such as Master thesis, publications or project reports.
Evaluation criteria:

  • Academic background (up to 40 points)
  • Knowledge and specific achievements (up to 35 points)
  • Shortlisted candidates will be invited for an interview in which the selection committee will assess the applicant’s communication skills, initiative, and motivation to pursue a PhD. (up to 25 points)

Deadline: April 26, 2023, at 23h59 CET (UTC + 01:00)
Enquiries about research content must be sent to the main PhD supervisor via email (see contact details in Supervisors section).

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