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instead that metal-like electronic materials could be built from two of the most abundant elements on Earth. Creating that possibility is the ambition of this project, and we are looking for a doctoral
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metallurgy or additive manufacturing; characterisation using advanced electron microscopy and x-ray diffraction techniques; mechanical testing using macro/micro-mechanical methods and failure investigation
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Foundation funding to build ELECTRA: a first-of-its-kind, AI-enabled automated laboratory for electron diffraction (MicroED) and structural elucidation that researchers anywhere in the country will be able
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subject. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability
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, cryogenic electron microscopy, and protein crystallography facilities. The laboratory has access to many exceptional Cores, facilitating basic research and drug development. The unique infrastructure includes
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etc). Advanced characterization of steels, for example transmission electron microscopy and electron backscatter diffraction (EBSD). Mechanical property testing. Materials modelling, with experience
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range of state-of-the-art structural biophysics platforms, including nuclear magnetic resonance (NMR), X-ray diffraction, mass spectrometry, electron microscopy, atomic force microscopy, and other
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eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview . Posting Summary The scientist will lead the Rutgers CryoEM & Nanoimaging Facility (RCNF), a regional core facility providing access
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facilities (X-ray diffraction, electron microscopy, chemical analysis, etc.) as well as dedicated investments in spectroscopy and crystal-growth equipment. The strengthening of the human resources devoted
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scanning probe and electron diffraction techniques for studying the adsorption of atoms, molecules and clusters on surfaces; commissioning and/or development of scientific instrumentation. programming skills