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fluorophore labeling, and biochemical/functional characterization of GPCRs, G-proteins, arrestins, and other signaling proteins. Perform single-molecule fluorescence (smFRET) imaging of labeled signaling
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of functional membrane proteins embedded in a micelle or lipid (nanodisc) environment Site-directed mutagenesis for site-specific incorporation of spectroscopic probes (e.g. spin labels or fluorescent labels
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for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your work as part of our UNT
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Laboratory. This is an opportunity to be part of a team helping with the design of new system software and runtime infrastructure to improve the performance and energy efficiency of future scientific computing
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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techniques. Preferred Qualifications: Knowledge of HPC matrix, tensor and graph algorithms. Knowledge of GPU CUDA and HIP programming Knowledge on distributed algorithms using MPI and other frameworks such as
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++/Python/CUDA programming for real-time image processing. Experience in MRI pulse sequence programming, ideally on Siemens MRI platforms. Experience in MRI image reconstruction; motion and distortion
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, the research group has a strong program in the synthesis and application of chemical probes in complex biological systems, with an emphasis on measuring probe labeling and phenotype-driven cell selection using
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in complex biological systems and measurements of probe labeling by LC-MS based proteomics, fluorescence microscopy, and cell sorting. Chemical Biology: We are hoping to extend our expertise by
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closure modeling and/or high performance computing environments (MPI, CUDA) • Expertise in software development and computing tools (C/C++, python, git, parallel computing, etc.) • Experience with deep