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Field
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, localised actuation produces large, global shape change. The project will investigate how to encode and control these instabilities in additively manufactured architectures, enabling robust “motion
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Technologies (Ireland); and a network-wide training program. Responsibilities and qualifications The PhD scholarship is on the topic of “Carbon-Aware Neural Architecture Search (NAS)”. Most AI models are built
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architecture (meta)materials for medical soft robotics applications. Furthermore, the morphology, microstructure, and mechanical behaviour of the metamaterials for soft robotics applications will be
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blocks into larger constructs, have emerged as promising avenues for cartilage regeneration. However, this typically results in a larger tissue with a disorganized matrix architecture, not resembling
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real‑time anonymization in practice. The researcher will develop hardware‑aware neural architectures with hardware-in-the-loop optimization and efficient inference strategies to meet the computational
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(Kirchhoff's laws) as soft or hard constraints, operational bounds (voltage limits, capacity, phase balance), and network topology through graph neural network architectures. You will build validated benchmark
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, Retrieval-Augmented Generation (RAG), agentic AI, software-defined vehicles, and AI-supported software engineering in collaboration with academic and industrial partners. Requirements A completed master's
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candidates hold a Master’s degree in Informatics, Mathematics, or a related field, and possess strong expertise in linear algebra, GPU architectures, and programming in C++ and Python. This is a 100% TVL E13
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tools for assessing material lifetime and performance, in connection with the data architectures developed within the REFFRACTEUR project. All modelling developments will be implemented in the open-source
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architecture (i.e. hydrogeological schematizations) that encompass the 3D variability in geohydrological properties. These models are to be validated using real-world monitoring data (e.g. on sand boils), and