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                , Urban Studies, Urban Analytics, Environmental Science, Computer Science, Architecture, or an appropriate master’s degree. Familiarity with Python/R programming, GIS and spatial analysis (e.g., ArcGIS 
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                contribute to the development of: An R package for path-space rejection sampling for diffusion processes. An R package for Bayesian Fusion pooling inference, such as privacy Bayesian Fusion and constraint 
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                an individual Resistant, Tolerant, or Susceptible (R/T/S) to a virus? That is the key question we aim to answer in this PhD study. We have gathered data on viral outbreaks over ~20 years and sequenced hundreds 
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                , Psychology, or a related field, to be awarded before March 1st, 2026. Essential skills include an ability to code (e.g., Python, R) and interpret data, knowledge of machine learning and statistics, and a 
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                of: An R package for path-space rejection sampling for diffusion processes An R package for Bayesian Fusion pooling inference, such as privacy Bayesian Fusion and constraint Bayesian Fusion The position is 
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                . Bioinformatics: Comparative genome analysis, detection of selection, and functional genomics, phylogenetics. Computational skills: UNIX/Linux, HPC computing, and programming in R and Python. You will gain hands 
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                on the topic (2,4). Training and Development Training will maximise future employability in academia and industry: Programming and geospatial data analysis using Python/R. Machine/deep learning techniques 
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                are looking for an enthusiastic individual with a degree in a quantitative discipline. Experience of geospatial analysis (with GIS) is essential and programming with code (e.g. R, Python) would be advantageous 
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                Title: Dynamic Processes in Organic Functional Materials Supervisors: Professor Paul R. McGonigal & Dr Alyssa-Jennifer Avestro Start date: 1st October 2026 Applications are invited for a DPhil 
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                interest and research in the field of economic and experience in data management and analysis. Demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar