We are looking for a candidate with a solid background in Machine Learning and intellectual curiosity in fact-checking, deep-fakes, and/or disinformation. Knowledge in topic modeling, argument mining, visual question answering, and sentiment analysis is a plus. Successful candidates must have demonstrated their ability to publish in top tier venues, such as NeurIPS, ICLR, CVPR, and/or EMNLP
The research is part of the Horizon Europe European Lighthouse of AI for Sustainability (ELIAS) project and will be conducted in collaboration with researchers at the Pioneer Centre for Artificial Intelligence,
The project supervisor is Professor Serge Belongie. The position is part of both the Pioneer Centre for AI and DIKU at the University of Copenhagen, offering a vibrant, international research community working across disciplines. DIKU is a member of the ELLIS unit Copenhagen, and Prof. Belongie is an ELLIS Fellow and Board Member. DIKU and the Pioneer Centre for AI offer its researchers generous support for career development, own fundraising, travel, and visitors, as well as support for and access to computing facilities.
The University of Copenhagen offers international researchers and their families a broad variety of services, such as support before and during relocation and career counselling to expat partners. Most international candidates qualify for a special foreign-researcher-tax scheme. Please find more information about these services as well as practical information on entering and working in Denmark here: https://ism.ku.dk/.
Copenhagen is continuously ranked among the most livable cities in the world with clean air, beautiful architecture, a rich cultural life and dedication to work-life balance and “hygge”. Employees are offered 6-weeks of vacation annually, generous parental leave and Copenhagen offers great childcare facilities, international schools and is a very family-friendly city.
Deadline: 1 February 2024.
More info and link to the application: https://candidate.hr-manager.net/ApplicationInit.aspx/?cid=1307&departmentId=18970&ProjectId=160592&MediaId=5&SkipAdvertisement=false