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computing subjects, including artificial intelligence. In addition, you will be able to demonstrate specialist expertise in one or more of the following areas: - Machine learning and deep learning
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position: Order-from-Disorder in Frustrated Quantum Magnets The Neutron
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models to real-world data (RWD). Create innovative tools and solutions to extract deeper
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applications, in part through investments in the software engineering, data science, and machine learning space. DSAI is focused on revolutionizing discovery by advancing artificial intelligence that evolves
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Neutral Infrastructure (dfCO2), this role contributes to Program 4: Machine Learning for Carbon Performance (https://dfco2.org.au/program_4 ) that aims to advance the next‑generation AI methods to model
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the interface of machine learning and biology (tools developed by the team: https://github.com/cantinilab ). The team is composed of 8 people : 3PhD students, 3 post doc, 1 research engineer and 1 assistant
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and collaborative environments. Required Education: PhD from an accredited college or university in Educational Technology, Learning Technologies, Human-Computer Interaction, or a related field
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(target journals: International Journal for Numerical Methods in Engineering – IJNME). Deep learning algorithms for high-temperature multiphase problems (target journals: Computer Methods in Applied
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for the BS Business and Technology Management, MS Management of Technology, MS Industrial Engineering, and PhD Human-Centered Technology Innovation and Design programs housed in the Department of Technology