If you would like a PDF copy of my full CV, please email me at g (dot) smith (at) ed.ac.uk.
Education
PhD at the University of Edinburgh, 2023-2027 (expected)
- A member of the competitive NERC-funded SENSE Centre for Doctoral Training
- Applying a machine learning model of glacier flow to estimate ice thickness of glaciers in High Mountain Asia, incorporating recent field data
- Collaborating with an international group of researchers on a rapidly evolving code base via GitHub
- Working with diverse geospatial data and a variety of analytical tools including QGIS and specialised Python packages including TensorFlow, xarray, and geopandas
- Communicating results to internal and external colleagues with a wide range of backgrounds, adapting communication style to fit the audience
MMath (Hons) Mathematics at the University of Edinburgh, 2016-2021
- Gained strong foundations in calculus, linear algebra, probability, and analysis before specialising in applied and computational mathematics, focusing on differential equations, algorithms, and numerical methods
- Received a College Vacation Scholarship to fund a summer research project
- Degree classification: first
Work experience
Data Science Intern at Earthwave Ltd, 2025.
- Small company providing satellite data platforms and services, with a focus on scientific research and algorithm development
- Implemented a novel method for spatiotemporal interpolation to fill gaps in geospatial data
- Followed company standards for unit testing and code formatting/linting
- Used a variety of industry-standard coding and machine learning tools such as Git/GitHub, Pytorch (and Pytorch Lightning), TensorBoard, Weights & Biases
- Worked in collaboration with other team members, responding to code reviews on GitHub
Analytical Scientist at MCS Ltd, 2022-2023.
- Consultancy company providing materials science and failure analysis services to a wide range of clients across the engineering sector, including large electronics and aerospace/defence companies.
- Adapted to various responsibilities within a fast-paced, small business environment
- Led the development and implementation of efficient data analysis workflows for microscope images, allowing the team to deliver results backed up by data
- Acted as project lead on many projects for our clients, managing colleagues to ensure results were delivered on time
- Engaged with external clients to provide solutions that met their requirements
Research Experience Placement at the School of Geosciences of the University of Edinburgh, funded by NERC through the E4 DTP, 2020.
- Competitive research placement scheme in environmental sciences
- Improving estimates of glacier thickness using satellite observations, a simple model of glacier dynamics, and MATLAB code
- Quickly acquired knowledge about a new topic, demonstrating learning ability
- Developed a lasting working relationship with a researcher in Geosciences