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Application deadline: 31/03/2026 Research theme: Nuclear Materials Hoe to apply: https://uom.link/pgr-apply-2425 UK only This 4-year PhD project is fully funded by the Nuclear Decommissioning
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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validation using advanced experimental techniques (such as mass spectrometry, electron microscopy, radiochemistry and radiobiology experiments with biomolecular and biological systems such as oligonucleotides
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. Profile We are looking for a candidate who has: A PhD in Physics, Chemistry, Biophysics, or a closely related field Experience with atomic force microscopy or related scanning probe techniques Background
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techniques, for example, at least some of: isothermal calorimetry, XRD, SEM, XRF, FTIR, NMR, TGA, electron microscopy and other solid-state and thermal analysis methods. Essential Application / Interview
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of complex materials such as rocks. - Extensive experience with electron microscopy (e.g. SEM and EMPA), Raman spectroscopy (e.g. phase identification) and X-ray diffractometry (e.g. for crystal structure
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electrodes using various electron microscopy techniques (e.g. FIB-SEM); (ii) Reconstruction of the 3D structure through image analysis; (iii) Analysis of images from new and aged membrane-electrode assemblies
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Neurobiology Unit at the GIGA-Stem cells, Liège, Belgium (https://www.gigaldn.uliege.be/cms/c_4226711/en/gigaldn ) Missions A PhD position is available to investigate the mechanisms underlying sensorineural
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validation using advanced experimental techniques (such as mass spectrometry, electron microscopy, radiochemistry and radiobiology experiments with biomolecular and biological systems such as oligonucleotides
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email. We are only accepting applications submitted by May 4, 2026. Quicklink for Posting https://uscjobs.sc.edu/postings/203768 EEO Statement The University of South Carolina does not discriminate in