Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
. Processing and analysing spectroscopic data using machine learning algorithms. Your primary workplace will be the VUB campus in Etterbeek, with occasional activities at the Brussels Photonics Campus in
-
and practical experience with modeling and machine learning software NONMEM, Monolix, Simcyp, PK-Sim, Gastroplus, R and/or Python is a plus You have excellent teaching and communication skills Any
-
analysis Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within an experimental team, with direct availability of experimental
-
analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
-
, machine learning) for energy applications, mostly focusing on reinforcement learning (RL), where you will consider innovative extensions (e.g., new neural network architectures) of state-of-the-art
-
(PSI), within the research group EAVISE. The project explores audio representation learning for low-resource settings. Recent advances in machine learning for audio have focused on learning
-
wireless communication, signal processing, digital, analog and mm-wave design, and machine learning. This is a unique opportunity to develop innovative, multi-disciplinary technology and shape future
-
machine learning algorithms for anomaly detection, pattern recognition, and efficient data compression. To ensure practical usability, these models will also be optimized to run efficiently on edge hardware
-
, Electrical Engineering, Aerospace Engineering or a related field, with a focus on Robotic Perception and learning based methods Demonstrated expertise in at least one of the following areas: Machine Learning
-
work actively on the preparation and defence of a PhD thesis in the crossroads between the fields of robotics, signal processing and machine learning The candidate will explore how graph-based