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electronics wastes. In this effort, the candidate will have a direct impact in informing the U.S. Department of Energy’s approach to e-waste recycling. The second approach involves supporting manufacturers and
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relative to career stage in high-quality peer-reviewed journals experience using relevant analytical techniques such as NMR, SEC, DSC, DMA, rheology or related methods evidence of the ability to undertake
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or similar platforms for version control, code management, and research data archiving. Demonstrated ability to collaborate effectively within interdisciplinary research teams and communicate scientific
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high-dimensional biological data. Preferred Experience developing deep learning models for multimodal biomedical data. Experience with imaging, single-cell, spatial transcriptomics, electronic health
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department description for applicable certification requirements Knowledge, Skills and Abilities: Learning Agility: Ability to learn new procedures, technologies, and protocols, and adapt to changing
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for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically
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. The incumbent will conduct research within the predetermined research scope and methodology, focusing on the field of power electronics. ● Lead/support projects for high-density power converter and
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qualitative and quantitative research methodologies Experience conducting co-design and consumer-engaged research. Proven ability to manage research projects and work independently while contributing
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skills and experience; strong computer skills including Excel, statistical and/or graphical software (ex. Adobe Illustrator, ImageJ, Powerpoint); excellent organizational and communication skills; ability
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. The incumbent will conduct research within the predetermined research scope and methodology, focusing on the field of power electronics. ● Lead/support projects for high-density power converter and