Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
funded research project “Navigating volatility in different welfare state contexts (VOLARE)”. This project analyses how social policy design interacts with the month-to-month income variability experienced
-
your interactions with colleagues. You actively contribute to the overall functioning and practical organisation of the department. You will join a team that strongly values collaboration, knowledge
-
effects of micro-profiling and patterned perforations on the structural performance of roof sheeting. In addition, the position involves experimental studies on the interaction between roof sheeting and the
-
, remanufacturing, and recycling workflows.At the same time, Augmented and Virtual Reality (AR/VR) technologies have demonstrated strong potential to support complex manual operations by providing interactive, in
-
the design of these systems to withstand such events. This PhD project aims to improve understanding of how extreme waves interact with offshore floating solar platforms, with the goal of supporting safer and
-
automated coding) and qualitative approaches (e.g., focus group interviews) to explore adolescents’ real-time interactions with gender narratives in their digital world. The project will be conducted
-
close interaction with academic and industrial stakeholders. The ideal candidate: holds a Master's degree in Engineering Technology, Bioscience Engineering, or a related discipline. has a strong interest
-
data collection and analysis, including neuroimaging or behavioral data•Languages: Dutch is strongly preferred, as the project involves extensive interaction with Dutch-speaking participants; English
-
PhD in Computational Simulations of Turbulent Reaction Flows for Clean Energy and Sustainable Propul
machine-learning methods, you will analyze flame-turbulence interactions, pollutant formation, as well as unclosed terms relevant to LES modeling. The analysis involves the fluid dynamic as
-
We are seeking a motivated and creative PhD student to develop the next generation of AI-driven protein design methods that explicitly account for protein–lipid and protein–membrane interactions