266 algorithm-development-"https:"-"Foundation-for-Research-and-Technology-Hellas" PhD positions
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- Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy
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- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); yesterday published
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- Eindhoven University of Technology (TU/e); Published yesterday
- Empa
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- Monash University
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- Norwegian University of Life Sciences (NMBU)
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- Radboud University
- Susquehanna International Group
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Field
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic
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anticipated include imaging phantom-based evaluation of quantitative SPECT/CT; reconstruction algorithm development; establishing a secondary standards laboratory for unsealed source metrology through gamma
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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) Interpretable machine learning for network adaptation. In this thesis, the student will study how interpretable models and explainable learning algorithms could be used in real cellular networks for safe
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implementation of security provisioning algorithm in DFL environment Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » Communication
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. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data. The PhD position will focus on development a comprehensive and AI-driven platform
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
: Algorithm Validation and Use Case Demonstration (Months 27–36): This WP will first develop an integrated hardware–software testbed to systematically validate the performance of proposed solutions under
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these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph theory, discrete optimization and machine
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data preprocessing, algorithm development, and optimization techniques. Excellent communication skills in English. Prior experience with environmental or photocatalytic systems is a plus. A fully funded
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volumes in a reliable, repeatable, and automated way. This project aims to establish a data-driven, adaptive framework that develops artificial intelligence tools, integrated with advanced geostatistics