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Job description We seek a highly motivated postdoctoral researcher to develop and apply integrated workflows for in situ cryogenic electron tomography (cryo-ET). The project will focus on automating
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of thousands of molecules in our fully automated high biosafety screening facility CAPS-IT against multiple viruses. You will be responsible for the development and deployment of advanced machine learning models
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required, and hands-on experience in running the Oxford Nanopore sequencer is desirable. Experience in high-throughput culturomics is desirable. Experience in, or interest in, laboratory automation will be
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(systems automation and controls) and are able to undertake sophisticated system development works. If qualified for admission, the candidate may opt to pursue a higher degree on relevant subjects
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imaging, high-content or automated image analysis, mouse behavioral assays, bioinformatics/omics analysis including scRNA-seq or ATAC-seq, and AI-assisted data analysis. Experience with mouse behavioral
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scientific programming languages is a plus. Excellent oral and written communication skills. Experience with automation, control, and instrument infrastructure. Ability to model Argonne’s core values of impact
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system dynamic and transient simulations. Integrate post-processing measures for simulations to help with automation. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our
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management, global and sustainable supply chains, retail distribution, automation technology for materials handling, purchasing and supplier development. This position is part will be part of the newly formed
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throughout the selection process, via automated emails from our e-recruitment system. Please check your spam/junk folder periodically to make sure you have not missed any of our updates. What to Submit All
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will work in the group led by Professor Paolo Monti, whose research focuses on transport network design, resilience, and AI-driven network automation for 5G and 6G infrastructures. About the research