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by recent deepfake misuse and strict regulations such as GDPR. We aim to develop a real‑time, privacy‑preserving camera system that anonymizes individuals directly on the device. Instead of blurring
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position The Laboratory of Causal Systems Immunology is looking for a PhD student or postdoctoral researcher to advance in vivo perturbational screening. We have developed single-cell CRISPR technologies
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collaboration with the plant scientists and computational biologists at PSB, you will develop solutions to extract information from a wide variety of biological imaging data using state-of-the-art computer vision
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position The lab is looking for a postdoc to further develop agentic pipelines that autonomously manage computational tasks: You oversee dozens of computational biology tasks across biological disciplines
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of virtualizing and forecasting the evolution of the radio-electric environment. In the second phase, the candidate will investigate machine learning and AI-driven algorithms for NTN channel prediction, enabling
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to trust. By contrast, symbolic approaches have reliability and explainability "built in", since they are based on logical reasoning. This motivates the development of neurosymbolic approaches as a way of
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researchers at IDLab. You will develop novel theoretical frameworks and signal processing techniques (traditional and/or AI based) for Near-Field ISAC in distributed cell-free 6G networks. The research will
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simultaneously provide reliable wireless connectivity and high-precision sensing. The objective is to develop localisation and sensing algorithms that achieve near-GNSS accuracy while improving robustness, energy
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algorithms developed within the projectValidate the sensing platform through laboratory and field experimentsCollaborate with project partners on system integration and testingPrepare technical documentation
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primarily on the development, validation, and implementation of the Psychological Referral Optimization algorithm (PRO). PRO is a brief digital e-screening tool designed to support early identification, risk