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; probabilistic program logics; logical relations for relational reasoning about safety, liveness, and security properties; formal modeling of low-level capability machines and secure compilation; program logics
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project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer engineering
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Netherlands. The Post Docs will be involved in all parts and activities of the research projects. The workload will be geared towards participation in coordination activities, data collection and data analysis, learning
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to collaborate with industry partners, teach at undergraduate and graduate levels, and supervise Master's, and PhD students. Candidates will become part of a collaborative work environment within and outside QGG
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer
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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make energy districts and communities more sustainable? We are looking for a highly motivated and
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engineering, with a strong willingness to learn the complementary skill set. Experience in collaborative research environments. Excellent communication and teamwork skills. A proactive attitude towards learning
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formation and changes occurring during processing and digestion. The starting date is November 1, 2025, or as soon as possible hereafter. The research project This post-doctoral position is part of the EU
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offer a unique opportunity to contribute to high-impact research in drones, AI, and human-computer interaction. Successful candidates will join a dynamic and inspiring international research environment