Sort by
Refine Your Search
-
Listed
-
Employer
- Delft University of Technology (TU Delft)
- University of Amsterdam (UvA)
- Eindhoven University of Technology (TU/e)
- European Space Agency
- Utrecht University
- AMOLF
- Amsterdam UMC
- Leiden University
- Nature Careers
- University of Twente
- Vrije Universiteit Amsterdam (VU)
- Wageningen University & Research
- 2 more »
- « less
-
Field
-
engineering using genetic modification can solve some of these problems, but introduces regulatory complexities and biological challenges of it’s own. Epigenetic editing, the controlled reprogramming
-
-design research, policy analysis, discourse analysis), and the ability to design and independently execute complex empirical research projects; excellent analytical and theoretical skills, including
-
societies govern complex human, animal and environmental health challenges? Do you enjoy working across disciplines, engaging with diverse partners, and translating research into actionable strategies
-
those skills to complex cultural questions. The fulltime position is for 18 months, starting May 1st, 2026. The project is funded by CLICKNL. What are you going to do Construct and analyze longitudinal
-
the local electricity system, while acquiring academic perspectives? Information This position is dual fold and has both a teaching and a research related aspect. Power networks are critical
-
to ESA’s strategy; a wide network of relationships and collaboration with top academics, industry and research centres; the opportunity to contribute to the Φ-lab strategy and activities. As an internal
-
stakeholders, including conducting a Delphi study to establish shared principles and system boundaries; analysing and interpreting existing LCA, HTA and healthcare datasets, translating complex data
-
(Faculty of Civil Engineering and Geosciences) and work closely with Dr Louise Nuijens and an (inter)national network of collaborators. QUASI offers a unique opportunity to combine cutting edge observations
-
(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
-
collaboration and design-based research. Interest in the hydrogen sector and energy transition. Ability to analyse complex challenges and translate them into actionable insights. Excellent analytical