My research has required me to develop a diverse toolkit of skills that are fundamental for tackling many problems in Geophysics, and that also happen to be very in demand in industry right now! To help you develop, and find a job, I’ll help you develop a good working knowledge of these skills.
Numerical Methods. The discoveries of the future will most likely require computationally-intensive numerical models and/or the application of numerical methods to very large datasets to push the boundaries of knowledge forward. I spend a lot of time applying numerical methods to modeling the generation and propagation of waves in the solid earth and atmosphere, to processing large datasets, and to ‘inverting’ observations to improve our understanding of the solid earth or atmosphere.
Signal Processing. In Geophysics we make extensive use of signal processing techniques, many of which were developed in the fields of mathematics and electrical engineering (and many of which were also developed by Geophysicists!). I apply signal processing techniques to seismic and geoacoustic data in order to extract signals from noise, and to measure key signal properties such as the direction of arrival.
Statistics. Uncertainty is inherent in Geophysics because, in practice, we never have enough data! That means we have to use statistical methods to capture uncertainty properly. Capturing uncertainty sounds boring, but it’s integral in understanding and interpreting our data, and really important when making real-world decisions based on our science. I’ve learned statistical methods from mentors at the national laboratories and apply these to many problems, such as how we can locate earthquakes, how we capture the uncertainty in numerical models of wave propagation, and how we present decision makers with scientific results.
Writing code. An important component of most of the work I do involves writing code. I’m a big proponent of the importance of using best-practices in writing code, even when doing fundamental research. I’ve had to learn these skills on-the-job, but have benefited from working with teams of computer scientists at the national labs.