Sort by
Refine Your Search
-
Category
-
Employer
- Delft University of Technology
- AcademicTransfer
- Eindhoven University of Technology
- Radboud University
- Eindhoven University of Technology (TU/e)
- University of Groningen
- University of Amsterdam
- Maastricht University (UM)
- Delft University of Technology (TU Delft)
- Leiden University
- University of Amsterdam (UvA)
- University of Twente (UT)
- Vrije Universiteit Amsterdam (VU)
- Wageningen University & Research
- Wageningen University and Research Center
- Amsterdam UMC
- University of Twente
- CWI
- Erasmus University Rotterdam (EUR)
- Radboud University Medical Center (Radboudumc)
- 10 more »
- « less
-
Field
-
to staff position within a Research Infrastructure? No Offer Description Are you passionate about doing research in mathematics? The Korteweg-de Vries Institute for Mathematics is looking
-
Are you passionate about doing research in mathematics? The Korteweg-de Vries Institute for Mathematics is looking for an ambitious PhD candidate in mathematics. Your research is part of
-
Do you love exploring new ideas and want to positively impact healthcare by developing new mathematical methods? We're seeking a motivated person to join us as a PhD researcher in our group
-
Job related to staff position within a Research Infrastructure? No Offer Description The Applied Probability research group within the Delft Institute of Applied Mathematics at TU Delft (see https
-
Irène Curie Fellowship No Department(s) Mathematics and Computer Science Reference number V32.7466 Job description As a PhD-TA candidate, you will work on new distributed algorithms for large
-
The Stochastics group at the Korteweg de Vries Institute at the University of Amsterdam and the Actuarial Science and Mathematical Finance group at the Amsterdam School of Economics are pleased
-
The Analysis research group within the Delft Institute of Applied Mathematics at TU Delft is offering a full-time PhD position in the area of Numerical Methods for Stochastic Differential Equations
-
the network vertices act independently by learning from their local observations. You will mathematically analyze the algorithms on random graph models and implement them on large real-life networks
-
, you will also work on analysing the theoretical properties of these algorithms using the mathematical framework of randomised complexity theory. You will be part of both the Probabilistic Graphical
-
consistency models. These models rest on a joint foundation of deep learning architectural research and mathematical theory. They therefore present an exciting research area for theoretically minded individuals