Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
: https://ece.au.dk What we offer The Department of Electrical and Computer Engineering offers: An exciting opportunity to work on cutting-edge research in IoT systems and critical infrastructure monitoring
-
of international researchers’ employment by AU . Please find more information about entering and working in Denmark here: http://international.au.dk/research/ An appointee who does not speak Danish will be required
-
funding calls in Plant2Food, through which the programme funds the best ideas from the matchmaking process. In your daily work, you will take the administrative lead to run Plant2Food successfully. You will
-
research profile within organisational studies, Computer-Supported Cooperative Work, Human-Computer Interaction or related research areas as documented by a PhD dissertation and/or research publications
-
processes. You will work experimentally with already established experiments including lysimeter trials, and you will have the opportunity to design and initiate new experiments. We expect that you will be
-
review process is provided below. The appointment will commence on 1 December 2026 or as soon as possible thereafter. The School of Communication and Culture is committed to diversity and welcomes all
-
for the tenure review criteria and for the tenure review process. Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment
-
26306659 Simon.wall@phys.au.dk Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the
-
(preferably with Python). 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
-
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