Sort by
Refine Your Search
-
Category
-
Employer
- Aalborg University
- University of Copenhagen
- Aarhus University
- Aalborg Universitet
- Technical University Of Denmark
- Copenhagen Business School
- Geological Survey of Denmark and Greenland (GEUS)
- Technical University of Denmark
- Graduate School of Arts, Aarhus University
- University of Southern Denmark (SDU)
- Technical University of Denmark (DTU)
- Technical University of Denmark;
- University of Southern Denmark
- University of Southern Denmark;
- 4 more »
- « less
-
Field
-
models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual sensing techniques (e.g., Kalman Filters) combined
-
models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual sensing techniques (e.g., Kalman Filters) combined
-
of novel methods to decompose the heterogeneity of psychiatric disorders, particularly ADHD, using large-scale genetic, imaging, and epidemiological data from Denmark and other countries. You will apply
-
The Department of Management at Aarhus University, School of Business and Social Sciences, invites candidates to apply for a position as research assistant. The successful candidates are expected
-
is available from 01 January 2027 or later. You can submit your application via the 'Apply' button above. Title PhD Position in Physical AI: Adaptive Foundation Models for Robotics Research area and
-
’ cognitive autonomy is at risk and how timely digital interventions can support independent thinking. Each PhD position is a three-year role and is funded by a DFF research project (‘Safeguarding Users
-
what this can tell us about their response to a warming climate? We are looking for a PhD fellow to reconstruct past changes in Greenland Ice Sheet melt and ocean conditions using marine sediment records
-
organisation and genome regulation. Using a combination of molecular biology, genome engineering, embryology and single-cell genomic approaches, the project aims to uncover the molecular mechanisms that ensure
-
utilizing earth-abundant metal catalysts (e.g., Mo, Fe, Co, Ni, Cu). These reactions will aim to transform abundant feedstock chemicals such as CO2 and biomass into high-value products using thermal
-
institutions maximize the utility of collected radiological data One of the major barriers to achieving this, is figuring out how to learn useful patterns in the data without relying on exhaustive labelling