Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
(24 months) but can be renewed for (up to) an additional year. The start date is May 15th, 2026 - or soon thereafter. The postdoctoral fellow will conduct research on learning theory problems related
-
Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
-
quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
-
The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
-
opportunity to join the ERC-funded project “ALPS - AI-based Learning for Physical Simulation”. Expected start date and duration of employment These are 1–year positions from 1 May 2026 or as soon possible. Job
-
in one or more of the languages taught at the department (French, German or Spanish). The successful applicant will strengthen the department’s focus on foreign-language teaching and learning at upper
-
implement state-of-the-art data science principles into dental practice. While our primary focus is on the use of deep learning in (dental) imaging, our work expands into any type of data (e.g. tabular data
-
and technology comprehension tools for children investigating children’s understandings and conceptualisations of computational and AI-based systems designing and empirically studying learning
-
strengthen the department’s research and teaching environment in English-language communication and conference interpreting. The successful applicant will be expected to teach on the Master in Conference
-
International Office encourages students who have at least one year left of their studies in Denmark to apply for the position. Please note that you need to be a full-time student at a higher learning institution