Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Antwerp
- Ghent University
- Nature Careers
- VIB
- Université libre de Bruxelles (ULB)
- Vrije Universiteit Brussel
- KU LEUVEN
- Vrije Universiteit Brussel (VUB)
- Hasselt University
- VUB Vrije Universiteit Brussel
- Bio Base Europe Pilot Plant
- Hewlett Packard Enterprise
- IMEC
- Institute of Tropical Medicine (ITM)
- KU Leuven
- King's College London
- Lafontaine Lab - Université libre de Bruxelles
- ULiege
- UNamur - Lab of F. De Laender
- University of Liège (ULiège)
- Université Libre de Bruxelles (ULB)
- Université catholique de Louvain
- Université de Liège
- Université libre de Bruxelles
- 14 more »
- « less
-
Field
-
palaces. We will achieve this via a multidisciplinary survey of a wide range of organic materials and objects of faunal and floral origins. In order to reconstruct the workflows of how these organic objects
-
to work on selective spectral microscopic imaging (SSMI) for in-situ sensing applications. Many emerging applications, including microplastic detection, food safety, bioimaging, and materials analysis
-
), led by Prof. Djamila Aouada, to pursue a PhD in Computer Vision with a focus on Media Forensics and Deepfake Detection. The candidate will conduct research on predefined topics contributing to SnT's and
-
to conduct research on the interaction between large language models, automated science, and innovation. In this context, large language models can serve both as a tool within the research and as the object
-
in mechatronic hardware and software You have a solid foundation in probability and statistics for Bayesian modelling, uncertainty quantification, and causal inference You have a team player mindset, a
-
or more of the following: ecological modelling, dynamical systems, network analysis, Bayesian statistics or probabilistic modelling, mathematical biology, multivariate data analysis. Interest in connecting
-
in mechatronic hardware and software You have a solid foundation in probability and statistics for Bayesian modelling, uncertainty quantification, and causal inference You have a team player mindset, a
-
deep experience with PyTorch, JAX, or TensorFlow. Broad knowledge of modern ML and optimization (gradient‑based, evolutionary, Bayesian, reinforcement learning). Hands‑on experience with generative
-
years. As one of the objectives of the assistant's mandate is to carry out and complete a doctoral thesis, the tasks will be divided equally between 'Teaching' and 'Research'. These may be reviewed
-
study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models