Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Groningen
- Leiden University
- Wageningen University and Research Center
- University of Twente
- Utrecht University
- Leiden University; Leiden
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- Radboud University
- Maastricht University (UM)
- Maastricht University (UM); Maastricht
- University of Twente (UT)
- CWI
- University of Twente (UT); Enschede
- Wageningen University & Research
- Wetsus - European centre of excellence for sustainable water technology
- Delft University of Technology (TU Delft)
- KNAW
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); Amsterdam
- University of Groningen; Groningen
- Vrije Universiteit Amsterdam (VU)
- Delft University of Technology (TU Delft); Delft
- Erasmus University Rotterdam
- Wageningen University & Research; Wageningen
- Amsterdam UMC
- Amsterdam UMC; Amsterdam
- Delft University of Technology
- Erasmus MC (University Medical Center Rotterdam)
- Radboud Universiteit
- Royal Netherlands Academy of Arts and Sciences (KNAW)
- Tilburg University
- Tilburg University; Tilburg
- VU Amsterdam
- Vrije Universiteit Amsterdam (VU); Amsterdam
- 25 more »
- « less
-
Field
-
), sustainable, and climate-adaptive crops. By combining plant biology, simulation modelling, and artificial intelligence we aim to develop smart breeding and cultivation methods. Thus, we try to speed up
-
on accurate constitutive models that describe the behavior of the molten material during forming. With the increasing demand for more complex components, a step change in model accuracy and associated material
-
Manufacturing (AM) is increasingly applied in repair and remanufacturing; however, integrating AM into supply chains demands new models and methods. In this PhD project, you will: develop dynamic supply chain
-
handling, enabling first-time-right manufacturing. The predictive quality of these tools relies on accurate constitutive models that describe the behavior of the molten material during forming. With
-
design and material handling, enabling first-time-right manufacturing. The predictive quality of these tools relies on accurate constitutive models that describe the behavior of the molten material during
-
, practitioners and researchers have realized that predictions made by machine learning models should be transparent and intelligible. Although explainable AI methods can shed some light on the inner workings
-
years, practitioners and researchers have realized that predictions made by machine learning models should be transparent and intelligible. Although explainable AI methods can shed some light on the inner
-
simulations. Job Description Are you passionate about bridging computational modeling with clinical cardiology to solve real-world healthcare challenges? We're seeking a PhD candidate to develop innovative
-
networks in vitro that severe mental disorders, such as the model SNAREopathies are a diverse group of brain disorders caused by mutations in eight genes that together drive the secretion of chemical signals
-
for effective water resource management, climate modeling, and agricultural planning. Despite its importance, accurately monitoring evaporation remains a major scientific challenge due to the complexity