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detector projects at Jefferson Lab and towards the Electron-Ion Collider, with some flexibility to pursue your own research interests. We seek candidates with a background in experimental nuclear or high
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experts across system software, power management infrastructure, performance characterization, networking, and novel computer architectures and accelerators. It will also involve collaboration with leading
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, for lithium-sulfur batteries is required. Additionally, the candidate will employ advanced characterization techniques, such as electron microscopy and synchrotron X-ray probes, to gain mechanistic insights
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. High-resolution tomographic measurements at a synchrotron facility aim to complement electron microscopy measurements. Research will be conducted at 2-BM, a fast micro-tomography beamline. Achieving sub
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-CCE Scaling Machine Learning. The HEP Division performs cutting-edge research facilitated through advanced detector development, high-performance supercomputing (HPC), and innovative electronic and
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computer vision. Experience with multi-modal data fusion and alignment techniques. Experience with spatial transcriptomics or other -omics data analysis. Proficiency in Python programming and scientific
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such as microelectronics and self-assembly of nanocomposites. Therefore, we seek highly motivated candidates to drive the project independently while interacting closely with senior members of the research
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) and in-house capabilities (e.g., scanning probe microscopy, optical holographic imaging, scanning electron microscopy). The work involves designing and performing experiments, interpretation and
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completed. Knowledge of x-ray/optical/electron physics, including diffraction, optics, detectors, scattering etc. Experience with deep learning (DL) libraries such as Tensorflow, PyTorch, JAX etc. Experience
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geometry manipulation with computer-aided design software. Experience with coupling CFD and FEA codes. Knowledge of multi-dimensional code development (in C++/C/Fortran) for two-phase/multiphase flow and