61 phd-machine-learning PhD positions in Belgium

PhD Student Causal Machine Learning

seeks to enhance the robustness and efficiency of debiased machine learning methods. This PhD project will primarily focus on this latter component, in interaction with fellow researchers on this project

PhD Position in Multimodal Machine Learning in Healthcare

of older persons. The candidate will also contribute to teaching activities related to machine learning or other areas depending on the candidate’s profile. Moreover, the candidate is a team player that

PhD student: Machine learning in plant regulatory genomics

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PhD position in explainable machine learning for reproductive medicine

fundamental knowledge of, this domain. Be sure to mention in your motivation letter any knowledge of (or previous experience with) the machine learning research topics of the PhD project as detailed in

PhD position: Machine Learning & AI methods for solver acceleration 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

PhD position in computational neuroscience and machine learning

. NERF is a joint research initiative by imec, VIB and KU Leuven. The project We are looking for a PhD candidate interested in developing machine learning methods and applying them to neuroscience problems

PhD student Causal Machine Learning

of debiased machine learning methods. This PhD project will primarily focus on the foundations of an assumption-lean modeling paradigm, with a strong focus on the analysis of repeated measures outcomes, in

PhD: AI for data-driven representation optimization for time series

Dept. ESAT of KU Leuven (Belgium) in the frame of the AI initiative of the Flemish Government. The goal of this research is to develop new machine learning methods for data-driven selection and

PhD position: Assessing and enhancing quality of time series data with AI methodologies

. ESAT of KU Leuven (Belgium). The goal of this research is to develop new machine learning methods for the quality assessment and enhancement of signals and annotations in time series data, with

PhD positions in Sustainable Data-centric Control

to have a strong theoretical and numerical background in one or more of the following fields: Control theory and dynamical systems Theoretical Machine Learning Data science and information theory