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Field
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Week 40 Offer Starting Date 10 Jul 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure
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to national security and societal wellbeing, such as finance, education, civil infrastructure, agriculture, healthcare, entertainment, security, and government; inventing new algorithms, techniques, and
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across AI and both experimental and computational chemistry. This Hub will promote connectivity of the broader community, training, and networking, as well as funding state-of-the-art research. Based in
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exposure AI based algorithms to optimize the performance of integrated terrestrial and non-terrestrial networks (coverage, capacity, energy, exposure) Digital twin operation: dynamic environment-aware
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. Machine learning algorithms have been considered in many application domains, including Internet of Things (IoT) systems. The adoption of machine learning in these domains creates many new opportunities
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with agentic artificial workflows as well as a strong understanding of governance and security protocols for deploying AI solutions. Required Qualifications: • BS/MS in Computer Science, Engineering, or
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of Engineering programme as Associate Professor in AI and Computer Vision. You will play a central role in educating future engineers, combining deep technical expertise with close interaction with students in a
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collaboration, and advising • Mentor and advise students on academic and career development • Participate in departmental, college, and university service, including committee work, program assessment, and shared
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. Focus areas include: Post-Quantum Cryptography (PQC) – algorithm design, implementation, and migration Quantum Key Distribution (QKD) – system integration, deployment, and network operations Hybrid PQC
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algorithms for methane and carbon monoxide. We have various research projects with high-impact stakeholders focusing on methane emissions using the TROPOMI satellite data, also in conjunction with high spatial