Postdoc in Human-Centered Explainable Fact Checking

Natural Language Processing Section
Department of Computer Science
Faculty of Science
University of Copenhagen

The Natural Language Processing Section at the Department of Computer Science, Faculty of Science at University of Copenhagen is offering a postdoc position in Human-Centered Explainable Fact Checking commencing on 1 September 2023.

Description of the scientific environment
The Natural Language Processing Section provides a strong, international and diverse environment for research within core as well as emerging topics in natural language processing, natural language understanding, computational linguistics and multi-modal language processing. It is housed within the main Science Campus, which is centrally located in Copenhagen. The section came into effect on 1 January 2021 as a spin-off from the Machine Learning section, to which it still maintains close ties. Further information about research at the Department is available here: https://di.ku.dk/english/research/ . The successful candidate will join Isabelle Augenstein’s Natural Language Understanding research group (www.copenlu.com/ ). The Natural Language Processing research environment at the University of Copenhagen is internationally leading, as e.g. evidenced by it being ranked 2nd in Europe according to CSRankings.

Project description
The postdoc postion is offered in the context of an ERC Starting Grant held by Isabelle Augenstein on ‘Explainable and Robust Automatic Fact Checking (ExplainYourself)’. ERC Starting Grant is a highly competitive funding program by the European Research Council to support the most talented early-career scientists in Europe with funding for a period of 5 years for blue-skies research to build up or expand their research groups.

ExplainYourself proposes to study explainable automatic fact checking, the task of automatically predicting the veracity of textual claims using machine learning (ML) methods, while also producing explanations about how the model arrived at the prediction. Automatic fact checking methods often use opaque deep neural network models, whose inner workings cannot easily be explained. Especially for complex tasks such as automatic fact checking, this hinders greater adoption, as it is unclear to users when the models’ predictions can be trusted. Existing explainable ML methods partly overcome this by reducing the task of explanation generation to highlighting the right rationale. While a good first step, this does not fully explain how a ML model arrived at a prediction. For knowledge intensive natural language understanding (NLU) tasks such as fact checking, a ML model needs to learn complex relationships between the claim, multiple evidence documents, and common sense knowledge in addition to retrieving the right evidence. There is currently no explainability method that aims to illuminate this highly complex process.

In addition, existing approaches are unable to produce diverse explanations, geared towards users with different information needs. ExplainYourself radically departs from existing work in proposing methods for explainable fact checking that more accurately reflect how fact checking models make decisions, and are useful to diverse groups of end users. It is expected that these innovations will apply to explanation generation for other knowledge-intensive NLU tasks, such as question answering or entity linking.

The project team will consist of the principle investigator, two PhD students and postdocs each, collaborators from CopeNLU as well as external collaborators.
The role of the postdoctoral researcher to be recruited in this call will be to research explainable fact checking with a focus on diverse user needs of end users in collaboration with the larger project team.

The principal investigator isProfessor Isabelle Augenstein, Department of Computer Science, e-mail: [email protected] . The postdoctoral researcher will further be collaborating with Professor Irina Shklovski, Department of Computer Science, email: [email protected] .

Job description

The position is available for a 2.5-year period initially. The key tasks of a postdoctoral researcher are:

• To plan and carry out research with increasing autonomy;
• To collaborate with researchers both within the research group, and with external project partners;
• To write scientific articles;

• To disseminate research nationally and internationally.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates.

Formal requirements
Applicants should hold a MSc degree or equivalent in Computer Science or a related field, and have good written and oral English skills. The assessment of your qualifications will also be made based on previous scientific publications (if any) and relevant work experience. The ideal candidate would have a prior research experience at the intersection of NLP, explainability and human-centered ML.

Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Danish Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State.

Negotiation for salary supplement is possible.

The application, in English, must be submitted electronically by clicking APPLY NOW below.

Please include:

• Cover Letter, detailing your motivation and background for applying for this postdoc position;
• Curriculum vitae;
• Research plan – description of current and future research plans;
• Diplomas (Master and PhD degree or equivalent);
• Complete publication list;
• Separate reprints of 3 particularly relevant papers.

The deadline for applications is Wednesday, 1 March 2023, 23:59 GMT +1.

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ .

Enquiries
For specific information about the PhD scholarship, please contact the principal investigator, Professor Isabelle Augenstein, Department of Computer Science, [email protected] .

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ .

Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.