Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
(Numerical Analysis and Applied Mathematics) develops numerical algorithms and software for large-scale problems in science and engineering. Its research ranges from algorithm design and analysis to software
-
that reduce raw data at the sensor level. You will develop AI and machine learning algorithms for anomaly detection, pattern recognition, and efficient data compression. To ensure practical usability
-
further developing algorithms and writing an application to develop a wearable device functionality for monitoring patient behavior monitoring based on the gained insights. We value candidates who: have
-
. Setting up, and testing optical spectroscopic measurement systems. Processing and analysing spectroscopic data using machine learning algorithms. Your primary workplace will be the VUB campus in Etterbeek
-
manner, and (2) design AI approaches such as learning algorithms and reasoning engines that can exploit the provided knowledge? The successful candidate will conduct research on how to build software
-
systems and signal processing Responsibilities: Design of optical setup Optical system analysis and simulation Material characterization Developing AI/ML algorithms Literature review and preparation
-
fundamentals of networking. Objectives: To achieve on-device spectrum sensing using on-board sensors of mobile BSs, empowered by embedded deep learning algorithms; to propose an analytical model for the cell
-
for photocatalytic degradation and H2 production.Designing multi-objective optimization algorithms to maximize environmental and economic performance. Your RoleAs a PhD researcher, you will: Build and validate hybrid
-
multimodal fusion, robust pose estimation, and real-time processing. Together, these roles form a cohesive effort to bridge algorithmic innovation with practical applications in next-generation media
-
, investigating novel methods for photorealistic scene reconstruction and understanding. Together, these roles form a cohesive effort to bridge algorithmic innovation with practical applications in next-generation