Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
-
Field
-
Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for: PhD Candidate, Reinforcement Learning for Sustainable Energy This position is embedded
-
scholars who have made valuable and innovative contributions to science or scientific practice. These contributions may relate to the themes identified in the Recognition & Rewards programme : research
-
newly collected survey data, which you will link to CBS register data, using advanced statistical methods. The data collection will be executed by KBA in collaboration with NCO, but you will be involved
-
MMF/Nexus pipeline and the stochastic Bayesian Bisous method. To improve, extend and deepen the analysis to a full dynamical inventory, a major incentive for the project is the application and
-
assisting in courses. Requirements Desired profile A master degree in computer science, artificial intelligence, or (very) similar. Self-drive, creativity, rigor, sense of ownership, and excitement to push
-
health behaviour. Using a novel combination of deep learning, street view imagery, and epidemiological methods, we aim to identify the most effective urban exposure modifications. This research will
-
Fellowship Programme (EVOLVE – EVOLVE Fellowship Programme), an initiative by six world-leading research institutes of two universities in The Netherlands (University of Groningen, Leiden University) to study
-
that are still largely controlled with insecticides. Alternative, more sustainable methods to combat these pest are desperately needed. Plants harbour diverse and dynamic microbial communities in and around their
-
methods to administrative data. The exact topic will be chosen in coordination between the successful candidate and supervisors. The successful candidate will be part of the Strategy Economics group within
-
Apply now The Mathematical Institute (MI) of Leiden University and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a PhD Candidate in Random Graphs and Complex Networks