Postdoc position ”REMAX: Rigorous Evaluation Methods for AI Explainability\" at Computer Science, Aarhus University

Technical Sciences - Center for the Theory of Inte; Denmark; On-site; DKK 480,000 - 560,000; Full time

Job summary

The Department of Computer Science at Aarhus University invites applications for a 24-month Postdoctoral Research Fellow in Explainable AI, joining the REMAX project on rigorous evaluation methods for AI explainability.

Based in the Data-Intensive Systems group, you will work at the intersection of computer science and philosophy, develop normative criteria, and create metrics and algorithms to advance XAI research. Applicants must hold a PhD with publications in ML/DM.

Qualifications

• Applicants must hold or expect to complete a relevant PhD degree with documented expertise in devising and analyzing AI models, preferably including XAI methods.
• A track record including publications in renowned ML and Data Mining venues is expected.

Education

PhD degree in a relevant field

Job description

Postdoc position ”REMAX: Rigorous Evaluation Methods for AI Explainability\" at Computer Science, Aarhus University

Technical Sciences - Center for the Theory of Inte

The Department of Computer Science at Aarhus University invites applications for a 24-month Postdoctoral Research Fellow in Explainable AI interested in interdisciplinary research between computer science and philosophy.

The REMAX project on Rigorous Evaluation Methods for AI Explainability, funded by a Villum Synergy grant, aims to create methods for explainable AI and their rigorous evaluation. It is a collaboration between the Department of Computer Science and the Centre for Science Studies at Aarhus University, Denmark.

The position is available from 1 December 2026, or as soon as possible thereafter.

Explaining complex AI models is a key challenge for ethically responsible AI. Explainable AI (XAI) research aims to provide relevant information to assist developers and users in analyzing AI models.

However, rigorous methods for evaluating XAI algorithms are currently lacking. This is in large part due to a gap between how explainability is evaluated within computer science and philosophy. In computer science, explainability is mainly evaluated through data-driven metrics. While they provide some insights for developers, it is unclear whether existing metrics track any ethically relevant properties. Conversely, in philosophy, explainability is evaluated using normative criteria. While based on principled ethical analyses of why explainability matters, they are currently too abstract and provide little practical guidance for AI development or governance. To bridge this gap, our goal is to: (a) pioneer new normative criteria for AI explainability, drawing on theories of evidence and explanation in philosophy of science; (b) develop novel metrics and algorithms for AI explainability; and (c) create a tight feedback loop where (a) and (b) can iteratively refine each other.

As a postdoc, you will be based in the Data-Intensive Systems research group, under the guidance of Prof. Ira Assent, and part of the ADA (Algorithms, Data, and Artificial Intelligence) in the Department of Computer Science. You will draw on your expertise in models and algorithms for AI and XAI, to engage with our colleagues in Science Studies, headed by Assoc. Prof. Rune Nyrup, where you will have a secondary office space.

The Department of Computer Science at Aarhus University has a strong research and education profile that spans theoretical and practical computer science. The Data-Intensive Systems group studies management and analysis of complex data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing.

Aarhus University is the second-oldest and second-largest university in Denmark. Aarhus is the second-largest city in Denmark and is situated by the sea in East Jutland. Aarhus is a “young” city due to its proportionally large population of young inhabitants. Denmark offers an attractive work-life balance and work environment.

Applicants must hold or expect to complete a relevant PhD degree with documented expertise in devising and analyzing AI models, preferably including XAI methods, with a track record including publications in renowned venues of the Machine Learning and Data Mining field.

Your application should include a CV, list of publications, letters of recommendation, as well as a brief letter of motivation. The letter should include a description of your background as relevant to the REMAX project, a motivation for interdisciplinary collaboration, and a sketch of potential research ideas if any (in total max. 1000 words).

Place of Work

The place of work is Department of Computer Science at Aarhus University. We are located at Åbogade 34, 8200 Aarhus.

Contact information

For further information, please contact: Professor Ira Assent, [phone], [e-mail].

Deadline

Applications must be received no later than 30 September 2026.

Application procedure

Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment committee if necessary, – the head of department selects the candidates to be evaluated. All applicants will be notified whether or not their applications have been sent to an expert assessment committee for evaluation. The selected applicants will be informed about the composition of the committee, and each applicant is given the opportunity to comment on the part of the assessment that concerns him/her self.

Formalities and salary range

Natural Sciences refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation.

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found here.

Appointment shall in accordance with the collective labour agreement between the Danish Ministry of Taxation and the Danish Confederation of Professional Associations. Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities.

Salary and terms as agreed between the Danish Ministry of Taxation and the Confederation of Professional Unions at basic salary steps 4-8.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.

Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity.

Aarhus University offers a broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners. Read more here . Please find more information about entering and working in Denmark here.

Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here.

At the Faculty of Natural Science at Aarhus University, we strive to support our scientific staff in their career development. We focus on competency development and career clarification and want to make your opportunities transparent. On our website , you can find information on all types of scientific positions, as well as the entry criteria we use when assessing candidates. You can also read more about how we can assist you in your career planning and development.

The application must be submitted via Aarhus University’s recruitment system, which can be accessed under the job advertisement on Aarhus University's website.