7 machine-learning "https:" "https:" "https:" "https:" "https:" positions at University of Southern Denmark
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analysis, and basic feature engineering. Experience with Python or a similar programming language, and basic exposure to scientific computing or machine learning libraries, combined with an interest in
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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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of extrusion systems, reinforcement strategies, construction detailing, and construction scale experiments. RA3) Machine Learning and Optimisation for Digital Construction: Data-driven and simulation-based
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projects and execute these in collaboration with other colleagues. Preferably, the candidates have experience with: Robot control Safety-critical systems Machine learning and reinforcement learning
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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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computer science. The candidate is expected to have solid knowledge in most of the following areas: Robotics Control theory Deep Learning & Machine learning Modelling and control of soft/continuum robots Experience
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human