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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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methods (e.g., fluorescence, reflectance, or label-free modalities). Collaborate on development and optimization of imaging instrumentation and workflows. Perform tissue preparation, imaging, and data
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include expressing recombinant proteins in insect, mammalian, and E. coli cells; purifying proteins using FPLC systems; performing in vitro RNA transcription and labeling; carrying out in vitro assays
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global issues and making a difference to people's lives. We believe that inspiring our people to do outstanding things at Durham enables Durham people to do outstanding things in the world. Being a part of
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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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The AMBER project This post-doctoral position is part of the EU cofund research project AMBER, Advanced Multiscale Biological imaging using European Research infrastructures, will address scientific
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lattice field theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging
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noticeable and concealed anti-counterfeiting measures and technologies have been developed to combat counterfeiting. Perhaps the most well-known class of anti-counterfeiting labels are luminescent security
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processing magnetic resonance imaging (MRI), such as arterial spin labeling and diffusion tractography using programming scripts, such as Python and C++ Self-driven, motivated, and creative in designing image