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University of Bristol - Science and Engineering MSc Environmental Modelling and Data Analysis
University of Bristol - Science and Engineering

MSc Environmental Modelling and Data Analysis

Bristol, United Kingdom

1 up to 2 Years

English

Full time, Part time

25 Jul 2025*

Sep 2025

GBP 31,700 / per year **

On-Campus

* home applicants deadline: 8 August 2025

** overseas full-time tuition

Introduction

Numerical models and satellite observation are fundamental to understanding environmental systems and change. The MSc in Environmental Modelling and Data Analysis will provide you with the skills to go on to a career in this exciting area. You will learn how models of environmental processes are developed and applied across a range of areas including climate change, flooding, biogeochemistry and glaciers. You will gain an appreciation of all aspects of environmental modelling, ranging from the philosophy of model development, focusing on links to observations and uncertainty analysis, through to more practical aspects such as numerical approximation and algorithm development and testing.

The programme has close links to MSc in Geographical Data Science and Spatial Analytics, and both programmes enable students to develop skills in Geographical Information Systems, analysis of satellite observations and data science techniques more widely. Training in these areas will be complemented by hands-on learning aimed at developing your coding skills in scientific programming and high-performance computing (with access to Bristol's unique supercomputing facilities).

The School of Geographical Sciences is ranked first in the UK for 'Geography and environmental studies' research (THE analysis of REF 2021). The MSc is taught by world-leading researchers from the School's research groups in both physical geography and quantitative spatial science. It is closely linked to the School's research strand in Modelling and Geocomputation, which hosts seminars and workshops aimed at consolidating links between environmental modelling and data science.

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