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Field
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permeability selection in variant membrane chemistries. This work will run in parallel to experimental analysis conducted at the University of Exeter using synthetic vesicles to observe permeability
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, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights into these complex interactions. As part of this position, you will have the opportunity
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an exciting, emerging topic. The position will focus on integration and device fabrication based on combinations of 2D materials and freestanding complex oxides, aiming at discovering, engineering and unlocking
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statistics and uncertainty quantification (Bayesian analysis, data assimilation, Gaussian process modeling), and their application to complex systems modeling. Experience in developing and applying statistical
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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, the Department cooperates across faculties and with the interdisciplinary centres. In particular, the new interdisciplinary centre focused on complex environmental systems opens up significant opportunities
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, Biochemistry, or Biophysics. You should be driven, have experience in protein production, the analysis of interactions between macromolecules, and good background in structural biology and biophysics. Since your
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. The selected candidate will assist with projects involving analysis of longitudinal data with missing, correlated data, and truncated outcome data. Pursuit of independent research that aligns with the project
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responsible for the project Design, synthesis, and characterization of complex organic molecules which play a pivotal role in DNP, Employ advanced NMR/MRI methods for structural analysis and DNP-related studies
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-ray observatories, and involve complexity analysis on uniquely variable sources. Applicants with general experience related to these observatories, timing variability of compact sources, time domain