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discipline. Experience with deep learning framework PyTorch or similar. Strong background in machine learning, image or signal processing. Knowledge of SotA models for multi-modality and scene understanding
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sanctions throughout their lives. This project proposes a paradigm shift: rather than viewing sanctions as standalone events, we aim to examine their effects across the life course. Are you interested in
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, monitoring, and interfaces with external entities; consolidating key security findings — risks, vulnerabilities, and controls — into the overarching system security picture and ensuring the implementation
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evolve and maintain a European Earth Observation Ecosystem Reference Architecture (blueprint) for the 2030–2060 timeframe; preparing new architectures addressing the paradigm shifts in Earth observation
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these processes, inform targeted in vitro experiments, and help design better biomaterials and TE strategies that harness mechanics and geometry. As a PhD candidate, you will adopt and extend in-house homogenized
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-ground interfaces. CHIME mission: CHIME (Copernicus Hyperspectral Imaging Mission for the Environment) provides hyperspectral imaging data to support environmental monitoring, agriculture and climate
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line with cost, schedule, quality and security requirements; supporting the design, implementation, integration and validation of prototype and pre-operational services making use of EO data, AI/ML
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parameters based on paired visible-light and X-ray images. The developed techniques will be validated on real data. As a candidate, you must have a strong background in machine learning and computer vision, as
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, such as quantum sensors (Rydberg receivers, NV diamond sensors, etc.) and photonic sensors. You will also work on optical payloads based on more classical optical systems, including imagers and
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(University College Dublin) and Prof. Leo de Vreede (TU Delft). This position directly connects to DISRUPT’s planned work on efficient ML-based DPD, accelerator architecture, silicon tape-out, and prototype