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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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) Radio/physical-layer intelligence (e.g., channel estimation, CSI prediction, edge-deployable deep learning), or ii) Networking and control-plane intelligence (e.g., reinforcement learning for scheduling
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Description We are seeking a motivated new PhD candidate who wants to join an exciting collaborative research program within the VIB-Center for Inflammation Research between the Guilliams, Saelens
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Referensnummer IFM-2026-00053 Work assignments This PhD position focuses on methodological and computational development in cryo-electron microscopy (cryo-EM), with emphasis on image reconstruction
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Listen Published Tuesday 10 Mar 2026 Deadline Thursday 30 Apr 2026 Work area PhD Organisational unit Rotterdam School of Management (RSM) Salary € 3.059 - € 3.881 Employment 1 fte - 1 fte Abstract
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strong foundation in either data science, electronics, or systems engineering—with a deep curiosity to learn the others. Professional qualifications: Educational background: You hold an MSc in
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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The rapid growth of deep learning has come at an extraordinary environmental and computational cost, yet the standard training paradigm remains remarkably unchanged. Every sample is passed through
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cartilage tissue engineering? Are you driven to develop novel in silico frameworks that deepen mechanistic understanding of tissue growth and inform in vitro experiments? Then you might be our next PhD