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into answering counterfactual questions. Using remote sensing multimodal time-series data and Earth foundation model embeddings, you will design and develop causal machine learning models tailored for dynamic
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for expensive new dispatchable generation capacity, enable deeper renewable energy penetration, mitigate grid congestion, and reducing CO₂ emissions at national scale. In this PhD project, you will develop
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: Translate ML-based error-correction / DPD algorithms into hardware-friendly forms (model reduction, sparsity, quantization, fixed-point design). Design the architecture and RTL of a low-power accelerator that
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(algorithms), and statistics. During this project, you will develop new methods to construct phylogenetic networks and generalize mathematical frameworks of phylogenetic network classes to tackle related
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MRI appliance; Develop real-time system reconfiguration support using static and dynamic techniques leading to rapid conversion to the most optimal configuration for any specific patient-centric scan
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contests to facilitate the generation, development, and implementation of new products, services, processes, and business model ideas. However, out of a pool of submitted ideas, typically only a few will be
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of the observation receiver used to measure the transmitter output and extract distortion information. This position is part of the ERC Synergy DISRUPT project, which aims to develop new architectures for observing
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development of AI and avoiding its misuse. These issues might be exacerbated by the lack of formal guarantees in explaining the behavior of AI systems in terms of human-interpretable, high-level concepts. While
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28 Feb 2026 Job Information Organisation/Company Tilburg University Research Field Mathematics » Algorithms Mathematics » Applied mathematics Researcher Profile First Stage Researcher (R1
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1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD position 2 will focus on designing scalable