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contribute to the collaborative TQT research community. Principal Investigator: Na Young Kim Project Name: Solid-state analog Optimization Solver and Quantum Machine Learning (Theory) Research Area
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genomic approach to profile enhancer dependencies. Develop and optimize experimental workflows integrating scRNA-seq, scATAC-seq, and other single-cell omics. Interpret high-dimensional data in
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addresses major limitations in surgical force sensing and has strong potential for commercialization and clinical impact. Key Responsibilities Redesign and optimize a fiber-optic (FBG-based) force sensor
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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, policy, energy conversion, new business models, techno-economic and life cycle analyses, machine learning, optimization, AI, intelligent networks, among others. The PDF will join a project in collaboration
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many-body physics, spin dynamics, quantum simulation, quantum optimal control, quantum optics, atomic physics. Required Skills: PhD in a field of research related to experimental quantum physics Broad
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repertoires within the thymic niche. Identify molecular and signaling targets to guide the engineering of functional thymic environments and optimize T-cell output from pluripotent stem cell-derived progenitors
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the thymic niche. Identify molecular and signaling targets to guide the engineering of functional thymic environments and optimize T-cell output from pluripotent stem cell-derived progenitors. Automate
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. David Granville, the incumbent will be responsible for: Designing and implementing research plans and approaches, including in vitro studies, in vivo models, formulation optimization Facilitating other
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, formulation optimization Facilitating other projects in the laboratory If successful, playing a key role in the establishment of a new UBC spin-off company working with programs offered through UBC and