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imaging and spectroscopy. Experience with data analysis or the ability to perform basic biochemical work with proteins and DNA, e.g., fluorescence labelling, enzymatic reactions will be highly rated in
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imaging and spectroscopy. Experience with data analysis or the ability to perform basic biochemical work with proteins and DNA, e.g., fluorescence labelling, enzymatic reactions will be highly rated in
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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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separately labelled for the user. Systems will be tested with instruments of varying degrees of contamination with the identified partners. Technical challenges / skills. 1. Practical integration/adaptation
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implemented in the Fortran programming language, and it relies on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use
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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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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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facility belonging to SciLifeLab, part of a national infrastructure for research in life science. The creative and research-intense environment contributes to a broad knowledge-base as well as cutting-edge
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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