Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
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 19 May 2026 (23:59 Danish
-
manufacturing processes for construction, including data-driven, sensing, and behaviour-informed robotic workflows. • AREA 3: Low-carbon 3D concrete printing, including computational design, process optimisation
-
excellence, including publication and societal outreach. Perform experiments, mostly based on anaerobic digestion, to investigate the anaerobic granulation process in UASB reactors and other type of attached
-
recruitment process here The appointment process at Aalborg University involves a shortlisting process. You can read more about the shortlisting and appointment process here . The hiring process at Aalborg
-
bring strong research expertise and strong technical skills within remote sensing and ecology, notably lidar processing. The successful candidate should have: Required: A PhD degree with a publication
-
, at 11.59 PM/23.59 (CET/CEST) Assessment and selection process Applications will be assessed by an assessment committee. Shortlisting may be applied. Shortlisted candidates will receive a written assessment
-
the interfacial organic layer at the electrode surface to promote the selective reduction of CO₂ to syngas, ethanol, or ethylene. In addition, the scale-up of the most promising processes will be done using
-
of applications may be used in the initial selection process. Living and working in Denmark Foreign applicants will be offered Danish language training as part of the employment. The International Staff Office (ISO
-
For further information, please contact: Professor, Kasper Røjkjær Andersen, kra@mbg.au.dk. Deadline: 17 March 2026 Application procedure Shortlisting is used. This means that after the deadline
-
by the Danish EUDP project “RePower-HPC.” Future AI and high-performance computing (HPC) systems demand unprecedented power levels driven by massive data processing. A key challenge is enabling