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Requisition Id 16262 Overview: We are seeking a postdoctoral researcher to work at the intersection of tensor networks, quantum algorithms, scientific computing, topological physics, and quantum
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to develop an online framework for assessing fatigue, structural integrity, and operability of multiple floating offshore wind turbines, supported by computationally efficient learning algorithms with
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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: Equivalence checking of quantum circuits. This task will include the identification of suitable metrics for approximate equivalence and algorithms to efficiently compute approximation distances. A potential
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research, education, and services in data science, AI, and biomedical computation, building on existing institutional initiatives such as DAISI. The successful candidate will perform a variety of research
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Computer Engineering, Computer Science, or a related field from a prestigious institution. Extensive experience in deep learning, AI, computer vision, 3D reconstruction algorithms, and large-scale Pre
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multiple countries. The position offers a highly collaborative and interdisciplinary research environment. The successful candidate will be expected to: develop computational algorithms for time-dependent
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: Equivalence checking of quantum circuits. This task will include the identification of suitable metrics for approximate equivalence and algorithms to efficiently compute approximation distances. A potential
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: 25/02/2026 Job Description Algorithm Design and Core Development The central responsibility involves building a standalone program that houses complex optimization algorithms. These algorithms manage
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