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Field
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provide a scalable building block for gatemon qubits and other quantum circuits. In parallel, we will conduct various experiments on the silicide films to investigate the possible emergence of triplet
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at Aalto University School of Science, in collaboration with the groups in the National Center of Excellence “QMAT - Quantum materials”. In parallel, the NANO group is pursuing work on fractional Chern
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students. Qualifications: Required: PhD in Computer Science, AI, Data Science, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs
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. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in materials science, mechanical engineering
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team of undergraduate/postgraduate researchers. Candidates should be able to multitask parallel evolution experiments with phenotypic and genomic analyses. Job Duties and Responsibilities: Typical tasks
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on Earth. We have computational capabilities that are designed to process millions of tasks in parallel, allowing the entire body to function under extremely variable conditions. Our organ of vision
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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techniques with the constraints of silicon processes. In parallel, you will develop on-chip antenna structures, performing full-wave EM simulations and translating these designs into manufacturable layouts
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, parallel storage systems and scientific data management. Recent research project details and outcomes can be found in computer systems conference proceedings, such as HPCA, FAST, SC, DSN, HPDC, IPDPS, and
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commercial electronic design libraries, combining high-frequency circuit techniques with the constraints of silicon processes. In parallel, you will develop on-chip antenna structures, performing full-wave EM