82 machine-learning PhD positions at Università degli Studi di Napoli "Federico II" in Belgium

PhD Student Causal Machine Learning

-generating mechanism, integrating it with recent insights from debiased machine learning and causal inference. Besides laying foundations for a novel paradigm for causal/statistical modeling, this project

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 grant in Applied Physics, Neuromorphic Photonics and Ising Machines

, contains: Within the context of the Belgian funded EOS project “Photonic Ising machines” there is currently an open position at the Vrije Universiteit Brussel (VUB) for a PhD student in the field

PhD student Causal Machine Learning

insights from debiased machine learning and causal inference. Besides laying foundations for a novel paradigm for causal/statistical modeling, this project seeks to enhance the robustness and efficiency

PhD student: deep learning in genomics to decode cellular identities in the human brain

modeling, generative AI) Proficient in Python programming Experience with machine learning is a plus (e.g., PyTorch/Tensorflow/Keras) Experience with explainable AI (e.g., SHAP) is a plus Experience with

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