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Field
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modelling, data-driven approaches, and experimental validation. The project combines computational materials science with practical membrane design for electrochemical energy applications. PhD Position 1
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in Experimental Particle Physics (https://www.hep.manchester.ac.uk/study/ ). Our group (https://www.hep.manchester.ac.uk/ ) is one of the largest research groups in the UK with over 100 members
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Description Probing neural representations of speech, in parallel with experimental phonetic analysis of the same data (collected in the field); placing the results in the context of linguistic typology. In
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block within this process. You will be embedded both within an experimental and computational team, providing a unique atmosphere where there is expertise to develop the deep-learning models while having
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researcher) in the field of experimental physics/materials science who is interested in completing a PhD at the Institute of Technology of the University of Tartu! The PhD project, will focus on performing
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on: https://www.dges.gov.pt/pt/pagina/reconhecimento Workplan and the objectives to achieve: Study and continuous development of fatigue testing equipment under uniaxial regimes (tension–compression; torsion
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, including experiments at the local tandem accelerator facility as well as at national and international research infrastructures (https://ikp.uni-koeln.de/groups/wimmer/join-us ). YOUR TASKS » Participation
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
therapeutic strategies. This PhD project investigates extracellular matrix-related mechanisms underlying liver fibrosis in BA through a combination of clinical, translational, and experimental approaches
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processes that produce energy and raw materials. The Department of Reactive Transport is looking for a PhD Student (f/m/d) Experimental analysis of the sorption kinetics for radionuclides on sheet silicates
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methods such as high-throughput experimentation to expediate the syntheses (and bioanalysis) of life-saving pharmaceuticals. The subsequent data will then be used to populate machine learning models