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techniques (geomorphic mapping, TruPulse, DGPS/drone surveys), engineering geology methodologies (slope stability, rock strength assessment), coding (python/matlab data analysis and modelling) and transferable
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code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ)' as the programme of study You will then need to provide the following information in the ‘Further
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. Candidates must have proven ability to work with large datasets, coding with Python/Fortran/C++ and ideally experience with high-performance computing. Applicants from an industry background are encouraged
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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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, and community resilience across vulnerable deltas. We welcome applicants with quantitative aptitude and curiosity about rivers, hazards, and sustainability (training provided in GIS, coding, and
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related subject Previous coding experience (e.g. python, bash, matlab) Good administrative skills, and the ability to organise and prioritise workload Excellent interpersonal, oral and written communication
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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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subject Knowledge of neuroimaging, machine learning, and/or neurodevelopment Proven record of ability to conduct high quality research in relevant health related subject Previous coding experience (e.g
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of genomics and bioinformatics, giving the student access to cutting-edge training opportunities in coding, data science and fundamental principles of computational analysis. The student will receive
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can be submitted here . To be considered, the application must use “SCEBE1125” as project code. the advertised title as project title All applications must be received by 9 January 2026. Applicants who