Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
, ballistocardiography, and bio-radar) in combination with machine learning based algorithms for time series analysis into the whole OSA diagnosis and treatment pathway. During diagnosis unobtrusive sensors that can be
-
., machine learning, stochastic dynamic programming, simulation). Affinity with (food) supply chain management is preferred. To collaborate with and to co-supervise MSc thesis students and internship students
-
that activity-silent mechanisms, such as short-term synaptic plasticity, also play an important role. We will experimentally target these two mechanisms, using EEG in combination with machine learning to reveal
-
, creativity, rigor, ownership, and excitement to push research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, data management, and
-
of Amsterdam. Interested in developing fundamental machine learning techniques for tabular data to democratize insights from high-value structured data? Then this fully-funded 4-year PhD position starting Fall
-
applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning
-
faces. At the same time, reinforcement learning is a key technology in artificial intelligence and machine learning that set various state-of-the-art results. In the Reinforcement Learning Lab
-
methodologies, such as additive manufacturing, for projects within the centre and for space exploration; Developing new ideas around medical technologies, for example, using machine learning techniques to support
-
Education A master’s degree in telecommunications, electrical or computer engineering is required for this post. A PhD in a relevant domain would be considered a plus. Additional requirements General
-
mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant