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Assistant - JR Posting Type Student Hours/week: 12 Eligibility: Work study preferred but open to all students Semester 2025-2026 Academic Year Location Structural Eng. Teaching and Research Lab Detailed Work
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or other community organizations • Familiarity with statistical modeling (e.g. use of structural equation modeling, hierarchical linear modeling, regression analyses). • Interpersonal skills that foster
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microscopy, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand
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· High-throughput genome sequencing library construction (e.g. Illumina library preparations for RNA-seq, DNA-seq, ChIP-seq) · Long read sequencing (library prep and sequencing) with Oxford Nanopore
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should have an aptitude for semi-independent laboratory work, which is well supported by the dynamic academic structure of the department. The candidate will also have the opportunity to work with
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materials, with microwave metamaterial and device designs, to help develop a new class of reconfigurable electromagnetic structures. This will involve using various simulation programmes, both for mechanical
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phonons, magnons, and other emergent quasiparticles. The successful candidate will lead time-resolved X-ray diffraction experiments to reveal structural and electronic dynamics in condensed matter systems
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About the Role You will contribute to the construction and quality control of the ATLAS Inner Tracker (ITk). The ITk group at Queen Mary University of London has played a key role in the development
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Theory (DFT) calculations using established codes (e.g., VASP, FHI-aims). Demonstrated experience with traditional methods for modeling atomic site disorder, such as special quasi-random structures (SQS
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the area of Neurosciences and/or Network Analysis. Ability to perform advanced structural and functional image analysis. 6 years of experience in Neuroscience. Responsibilities Research Under general