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Field
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Mitigation Accelerated by Photons group led by Prof. Dr. Pelayo García de Arquer is searching for exceptional researchers, with an excellent proven track record, to work at the interface of materials science
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the impact of collective effects in high space-charge regimes. The Accelerators and Ion Sources Pole of LPSC is involved in the design, construction, and operation of the PERLE machine, particularly in
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?s success. Job Overview The P&G Digital Accelerator@UC is seeking a motivated PhD toxicologist or pharmacologist with expertise in transcriptomics for a 24-month post-doctoral position partnering with
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The Theory and Modeling Group at the Center for Nanoscale Materials (CNM), Argonne National Laboratory (near Chicago, Illinois), invites applications for a postdoctoral appointment focused on theory and simulation of the electronic structure of polycrystalline and defective two-dimensional...
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Posting Description POSTDOCTORAL ASSOCIATE, Mechanical Engineering - The Accelerated Materials Lab for Sustainability (AMLS), to lead the development of perovskite photovoltaic devices as part of a
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Engineering, is seeking a Postdoctoral Research Associate. This is a full-time position supported by a Department of Energy (DOE)-funded collaboration project between ASU and Fermi National Accelerator
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
://www.med.unc.edu/pharm/directory/yinglong-miao/) is looking for two highly motivated Postdoctoral fellows to work on accelerated molecular simulations and AI-driven drug discovery. Research projects in the Miao Lab
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Academy of Engineering Green Future Fellowship, the postholder will design and integrate automated experimental workflows and data pipelines to accelerate the discovery and optimisation of OPV devices
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Department Summary The Knight Campus for Accelerating Scientific Impact is an ambitious initiative designed to fast-track scientific discoveries into innovations that improve the quality of life for people in
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operando data related to battery degradation and safety. You will develop and implement advanced deep learning models to analyse multi-modal operando data from accelerated stress testing, with the aim