Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Ghent University
- KU Leuven
- University of Antwerp
- Vrije Universiteit Brussel (VUB)
- VIB
- IMEC
- Université libre de Bruxelles (ULB)
- Vrije Universiteit Brussel
- Hasselt University
- Nature Careers
- Royal Military Academy
- Université Catholique de Louvain (UCL)
- Université Libre de Bruxelles (ULB)
- Université de Namur
- Vlerick Business School
- Electronics and Informatics Department
- University of Liège (ULiège)
- Université catholique de Louvain
- Université catholique de Louvain (UCL)
- ; Katholieke Universiteit Leuven
- CEFIC - European Chemical Industry Council
- Gembloux Agro-Bio Tech
- LUCA School of Arts
- Siemens
- Sony
- UCLouvain
- University of Liege
- VUB
- 18 more »
- « less
-
Field
-
sound enhancement (Siemens Industry Software NV, Müller BBM, Trèves, Phononic Vibes, Saint-Gobain Ecophon, Tyréns, Purifi ApS). Doctoral Candidate 2 (DC2) within VAMOR will develop novel deep learning
-
in the field of medical image processing and analysis using deep learning. This position is part of the ERC Consolidator project “A data-driven approach to microstructure imaging” (ADAMI), funded by
-
applications (e.g., to enable wearable robotics to proactively respond to the user’s activities). Deep learning has enabled promising results in various applications by automatically discovering complex
-
Programme? HE Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD research aims to develop deep learning-based methods for bias correction of climate model
-
learning offer in the broad field of AI. The task package: You map out the existing supply. You support existing training programs where necessary. You identify gaps in the existing supply and identify ways
-
RNA-Seq, ChIP/DAP-Seq protein-DNA interaction data, bulk, and single-cell ATAC-Seq) and the application of diverse supervised machine learning approaches (e.g., feature-based, deep learning, and
-
within the IN-DEEP project you will be at the forefront of developingnew hybrid machine learning (ML) accelerated solvers. A fast-expandingarea of research is the application of ML techniques to predict
-
parts. First, the candidate will develop machine learning models to assist gynecologists and embryologists in their decisions and advice regarding couples with fertility problems. We will focus
-
Number AAP-2024-7 Is the Job related to staff position within a Research Infrastructure? No Offer Description We are excited to announce a postdoc (doctor-assistant) position in "Self-Supervised Learning
-
are currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning. In particular, we develop machine learning methods to derive