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that enable interpretable models to learn from deep representations. In this project, the researcher will develop theory and algorithms for (hybrid) model selection that allows to exploit domain knowledge
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that the programme will combine ideas from a broad range of disciplines, including machine learning, control theory, differential equations, port-Hamiltonian systems theory, modelling of power systems, digital signal
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will provide critical insights into how accents shape communication and behaviour in diverse contexts. Job description: The successful candidate will receive interdisciplinary training in theories and
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environment that brings together expertise in computational design, digital fabrication, and architectural history/theory. The project will be situated within ongoing explorations of robotic fabrication
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-based PhD program. The department has a strong commitment to theory development and innovative research, but we also prioritize the societal value of our research and devote ample time and attention
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knowledge Excellent communication skills Fluent in English (written and spoken) Why join us Interesting work in a diverse research environment, combining expertise in materials growth, transport and theory
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/or mathematical programming tools) applied to modelling agricultural and food policies and markets. Good knowledge of microeconomic theory and agricultural and food policies. Experience in using
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: Master's degree in Information Technology or equivalent education Knowledge of systems theory, systems modelling and simulation methods Knowledge of digital twin concepts, architectures, and applications
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Background Scholarship code: IND-25122 Expressions of interest - open until filled. This is an industry-linked PhD scholarship. This scholarship is created by La Trobe University in collaboration
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and complex materials challenges. HTS are strongly correlated systems with unconventional superconductivity, and their microscopic theory remains incomplete. They require doping to become