61 phd-machine-learning scholarships 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

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

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 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 candidate for Spatial multi-omics data integration

, probabilistic modelling, generative AI) or machine learning Proficient in Python or R programming Strong communication skills in English Desirable but not required Preference will be given to candidates with

PhD candidate at the intersection of Cell-Cell Communication models and Spatial Omics

systems biology Background in AI (deep learning, probabilistic modelling, generative AI) or machine learning Proficient in Python or R programming Strong communication skills in English Desirable but not

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 Research on Multi-Channel Acoustic Sensing for Autonomous Vehicles

have taken specialized courses in some of the following disciplines: digital signal processing, audio signal processing, machine learning, and/or machine listening. Research experience (e.g. through