Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
-
on developing and studying privacy-preserving methods, such as differential privacy, Bayesian privacy, federated learning and synthetic data. The aim is to enable meaningful analyses, such as identifying disease
-
degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
-
dissemination is expected to focus on leading Human-Computer Interaction venues. For further information about the project, see: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders
-
while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed
-
paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
-
paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
-
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
-
related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
-
estimation, and performance prediction. Build computationally efficient models suitable for monitoring, performance prediction, optimization, and control, and evaluate their accuracy, robustness, computational