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Field
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but not limited to: o Quantum error correction, fault tolerance, and resource optimization. o Entanglement dynamics, quantum control protocols, and hybrid quantum-classical algorithms. o Modeling and
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opportunity to develop cutting-edge AI-enhanced algorithms for analyzing transposable elements (TEs) in cancer epigenomics, with direct translational applications to precision oncology and immunotherapy
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algorithms for entanglement distribution in quantum networks. The purpose of the role is to contribute to the project "Utility Optimization in Quantum Networks: Algorithm Design and Analysis", working with Dr
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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
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foundations, focusing on the structure and complexity of quantum computational models; (ii) optimization and related graph-theoretic methods, using polyhedral geometry and algorithmic optimization (e.g., vertex
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algorithms for entanglement distribution in quantum networks. The purpose of the role is to contribute to the project “Utility Optimization in Quantum Networks: Algorithm Design and Analysis”, working with Dr
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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genomic graphs. The project will also deliver efficient algorithms to train these models under budget and time constraints, facilitating flexible adoption of the methods. The project is carried out in close
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will have the opportunity to develop innovative algorithms and models that integrate multiple data modalities, collaborate with industry partners, and contribute to high-impact publications. Job
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applications for a Post-Doctoral Associate position, in the area of Quantum Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects of quantum