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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 months ago
, further exploring the carbon-related impact of polymer breakdown. The project will also incorporate artificial intelligence (AI) and machine learning to optimise degradation processes and data analysis
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and data analysis. You will be working at the interface of chemistry and chemical engineering to improve the enrichment process. This will involve investigating different extractants, solvents, and
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their impact on bladder function under physiological and pathological conditions. Work will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human
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• Experimental investigations using atomic force microscopy (AFM), including force-distance curve-based imaging, (single molecule) force spectroscopy, nanomechanics, and associated data analysis • Application
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. This includes sample preparation, data collection, computational analysis, and 3D structure determination of protein macromolecules. Experience in cellular tomography workflows for EM analysis of cells and
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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scientific programming and numerical / statistical analysis of simulated and observed data. Candidates should be able to demonstrate motivation and a strong eagerness to learn, and have the ability to both
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microorganisms catalyze the freezing of cloud droplets. These substances are a significant source of so-called ice-nucleating particles, particularly over remote marine regions. The aim of the advertised PhD
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languages such as Python for data analysis and simulations. Experience with optical systems, astronomical observations, or satellite tracking would be advantageous, although not compulsory. Strong analytical
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Knowledge and experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl