HYBRIDS Doctoral Fellow

Department: School of Electronic Engineering & Computer Science
Salary: £45,174.92 per annum (inclusive of mobility fee and family allowance, where applicable).
Reference: 000000HYBRIDS-DC11
Location: Mile End
Date posted: 15 March 2023
Closing date: 26 April 2023

Overview

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 per annum (inclusive of mobility fee and family allowance, where applicable).

To view the job profile, click here

Objectives:

(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.

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.

For more detailed information and to apply go to the following link  https://hybridsproject.eu/jobs/dc11/

Reference number: HYBRIDS- DC11
Host institution: Queen Mary University of London , United Kingdom
PhD Enrolment: Queen Mary University of London, United Kingdom
Inter-sectoral Supervisors: Ms. Vindhya Singh and Ms. Stephanie Öttl, Industrieanlagen- Betriebsgesellschaft (IABG)