Research Assistant in Next Generation AI Explainability - DTU Compute

Are you passionate about explainable AI? DTU Compute's Section for Cognitive Systems invites applications for research assistant position to investigate the properties of deep learning representations and improve their interactivity.

Make AI explanations more understandable  
Machine learning algorithms often appear as complex black boxes and much research goes into visualizing the hidden representations learned from data. The communication aspect of explainable AI has so far attracted less attention. Do you want to help us make learned representations more interactive? 

The Cognitive Spaces project aims at making AI explanations more understandable, robust and trustworthy. Your part of the project will be to help demonstrate real-world usability of our methods. Our primary application area is modeling and decision making based on electric brain waves (EEG). 

Responsibilities and qualifications
Your main tasks will be design, implementation and analysis of AI experiments.

You should have:

• Experience in Python
• Experience with deep learning frameworks
• Interest in design and user test of explainable AI systems
• Interest in EEG
• High level of motivation and innovation
• Excellent communication skills in English

The research area is very active with many possibilities for collaboration and networking within academia, hospitals and there is a thriving start-up scene.

The position is funded by a Novo Nordisk Foundation data science grant: Cognitive Spaces – next generation explainability. 

As a formal qualification, you must have a master’s degree in engineering or equivalent.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. 

Salary and terms of employment 
The appointment will be based on the collective agreement with the Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. 

The period of employment is 6 months. Preferred start date would be 1 August, 2025 or according to agreement.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Professor Lars Kai Hansen, lkai@dtu.dk.

You can read more about DTU Compute at www.compute.dtu.dk. 

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.

Application procedure 
Your complete online application must be submitted no later than 18 June 2025 (23:59 Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• Application (cover letter)
• CV
• Academic Diplomas (MSc)

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

DTU Compute
DTU Compute – Department of Mathematics and Computer Science – is an internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and imple