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on developing, implementing, and applying tensor-network and related quantum-dynamics methods. Applicants may indicate a preference for one project or ask to be considered for both. The start date is flexible
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to start imminently, and before mid October this year. The project intended for the post-doc is part of a collaboration within my group on the Google Willow Chip project (https://www.bbc.co.uk/news/articles
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seeking to recruit a motivated Postdoctoral Researcher to work in the theory projects within the Centre of Excellence in Quantum Materials (https://www.qmat.fi ). The research will be guided by Professor
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from multi-omics datasets (epigenomics, transcription, sequence). • Using representation learning (tensor factorization framework e.g., AVOCADO) extend the predictive framework allowing imputation in
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on theoretical and computational aspects of quantum many-body systems, including Tensor Networks, Neural Quantum States, Stabilizer formalism, Complexity measures such as entanglement and quantum magic, quantum
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mid October this year. The project intended for the post-doc is part of a collaboration within my group on the Google Willow Chip project (https://www.bbc.co.uk/news/articles/cd7pwezyze1o) for which we
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on three main tasks. The first task is to perform centroid-moment tensor inversions for small (M < 1) induced events in the Groningen area, yielding valuable insight into the ability to invert waveforms
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tensors and local plastic strains (including operating slip systems) from Lab-4DµXRD data, in collaboration with the DTU Lab4DMade team and the Danish company Xnovo Technology ApS. Performing in situ Lab
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tensors and Taylor models as tools to map neural systems onto mathematically well-understood objects. Pioneering the field, the ACT has developed several innovations, including deep learning for guidance
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structure methods, quantum Monte Carlo, tensor networks, or quantum embedding methods, etc. - ML-augmented numerical method development. - High-performance computing (HPC