Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
research project with industrial partners, providing access to realistic system configurations, experimental setups and operational data. The scientific ambition is to develop methods that combine physical
-
machine learning methods to explore how meltwater — at the surface and at the ice sheet bed — is coupled to ice flow. Building on this, you will also examine how meltwater and ice dynamics influence
-
ecosystems. A particular focus will be on developing and applying environmental DNA (eDNA) methods for characterising and quantifying marine biodiversity, with an emphasis on marine macroalgae. This includes
-
Computing , Engineering Job Type Postdoctoral Employment - Hours Full time Duration Fixed term Qualification PhD Sector Academia Apply on website (This will open in a new window from which you will be
-
DTU Tenure Track Assistant Professor in Surface Physics and Catalysis for Sustainable Energy Solu...
using and developing state-of-the art methods and instrumentation. Our experimental facilities span ultra-high vacuum surface science, electrochemistry, thermal catalysis, and atomic-scale microscopy
-
affinity to computational methods and tools. The project is funded by a Carlsberg Foundation Semper Ardens: Accelerate grant, an ambitious funding instrument supporting research of high international
-
funded by the Pioneer Centre for Statistical and computational Methods for Advanced Research to Transform Biomedicine (SMARTbiomed). SMARTbiomed is an international collaboration between Aarhus
-
applicants to: Have solid knowledge of econometrics and applied quantitative methods, with experience using Python, R, Stata, or similar tools, and be eager to learn and apply new methods. Be
-
’). Research objectives This project develops methods to detect changes in users' cognitive load and designs digital interventions that support cognitive autonomy in human-AI interaction. The two PhD positions
-
contribute to the analysis and interpretation of monitoring and experimental data from coastal Greenland ecosystems. A particular focus will be on developing and applying environmental DNA (eDNA) methods