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following thematic areas: • AREA 1: Machine learning and AI-driven methods for design, simulation, and optimisation in architectural and construction engineering. • AREA 2: Robotic and additive
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
. Proficiency in at least two of the following programming languages: Python, R. Experience in Machine Learning and Computational RNA Biology are desirable. Hands-on experience or understanding (the limitations
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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intelligence, and research software engineering, and is interested in developing robust, transparent, and sustainable computational tools. Experience with first-principles electronic structure methods, machine
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enhance machine learning performance; novel chip design strategies prioritizing efficiency and cost; verification of digital designs; advancements in electronic design automation (EDA), especially for AI