106 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" PhD scholarships in Belgium
Sort by
Refine Your Search
-
Listed
-
Employer
- KU LEUVEN
- The Belgian Nuclear Research Centre
- VIB
- University of Antwerp
- Vrije Universiteit Brussel
- Ghent University
- Université Catholique de Louvain (UCLouvain)
- Vrije Universiteit Brussel (VUB)
- KU Leuven
- Université catholique de Louvain
- Lafontaine Lab - Université libre de Bruxelles
- Nature Careers
- University of Leuven
- University of Liege
- Université Catholique de Louvain (UCL)
- Université de Liège
- 6 more »
- « less
-
Field
-
, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
-
teacher education. Using Teach for All as a case-study, the project aims to better understand how and why education polices travel across time and space. While policy mobility is driven by a wide range of
-
) device is under development in collaboration with Université catholique de Louvain (UCL). In general, the PhD topic is targeting the development of a systematic dataset of thermal conductivity evolution in
-
12 Nov 2025 Job Information Organisation/Company Université Catholique de Louvain (UCL) Department Earth and Life Institute Research Field Agricultural sciences » Soil science Agricultural sciences
-
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
-
industrial Ph.D. position focused on developing scalable, Machine Learning (ML) pipelines for genomic and epigenomic biomarker discovery from Oxford Nanopore Technologies (ONT) long-read sequencing data
-
such as surgery, patient or staff scheduling using, e.g., multi-objective optimization or machine learning approaches and analyzing efficiency-fairness trade offs. The research will be conducted under
-
. These methods will integrate machine learning techniques and real-time sensor data, to enhance operational efficiency, reduce costs, and ensure desired service levels, such as meeting a high percentage of demand
-
both independently and as part of an international, interdisciplinary team Assets•Experience with computer vision or deep learning (e.g. PyTorch, TensorFlow)•Familiarity with street view imagery or other
-
breakthroughs in proof logging, where solvers do not just output an answer, but also a machine-verifiable proof (or certificate) of correctness. However, a major limitation of current techniques is that