Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
fields. The position is part of the project “Promoting healthy ageing through voluntary efforts” (ProHealth) led by Associate Professor (Promotion Program) Mette Kjærgaard Thomsen and funded by the Tryg
-
. This full-time position offers a unique opportunity to contribute to high-impact research in drones, AI, and human-computer interaction. Successful candidates will join a dynamic and inspiring international
-
of Computer Science. We provide an ambitious and supportive research environment focused on the design and evaluation of interactive systems that extend human cognitive, affective, and collaborative capabilities in
-
technologies, such as artificial intelligence, social computing, and mobile devices, impact both individual experiences and practices as well as collaboration within and across groups. How to apply Your
-
University (AAU) in Aalborg. This full-time position offers a unique opportunity to contribute to high-impact research in drones, AI, and human-computer interaction. Successful candidates will join a dynamic
-
advanced computational methods to improve and understand protein function Interest in entrepreneurship to make a positive impact on planetary and human health As a formal qualification, you must hold a PhD
-
, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer
-
initially for two years with the possibility of extension. We are seeking a highly motivated researcher who is excited to play a key role in developing an ambitious research programme and establishing
-
Job Description Migraine affects more than 15% of the global population and remains inadequately treated despite advances in biologics and receptor-targeting therapies. Emerging computational
-
at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum