My name is Jake Ward. I am a programmer and astrophysicist.
I studied Physics with Astrophysics at Leeds University where I received a BSc and an MSc. My masters thesis focused on using unsupervised machine learning methods to classify the spectra of massive protostars. I then moved to Keele University to study for my PhD where I worked primarily on high-resolution integral field spectroscopy of massive YSOs in the Magellanic Clouds.
After completing my PhD, I worked as a post-doc at Heidelberg University in Germany for three years. There my work mostly followed two branches: investigating the origins of OB associations using data from ESA’s Gaia mission, and developing the first multi-tracer timeline of star formation in the Large Magellanic Cloud.
Since May 2020 I have been working as a Junior Gameplay Programmer at Cloud Imperium Games.
I also have a keen interest in brewing beer and making cider as well as being a big fan of games (boardgames, video games, and roleplaying games). When I get the time, I sometimes blog about this sort of thing at my blog: beerandgaming.wordpress.com.
I have spent most of my professional life working as an astrophysicist. The focus of this work has been the physics of star formation across various spatial scales ranging from the cloud-scale physics of star formation averaged over entire galaxies down to the formation and evolution of individual young stellar objects.
Highlights of my work in research include constraining the relationship between metallicity and accretion rates in massive star formation, showing that OB associations are not the remnants of more compact clusters, and developing the first multi-tracer timeline of star formation. Details on this work can be found on this page, and my list of publications is here.
I am well versed in a number of languages including Python, IDL, Java, C#, and C++. Examples of some of my work can be found on my projects page.
I began by learning python while working on my masters thesis in order to test the performance of various unsupervised machine learning algorithms as a way to carry out automated classification of massive protostars. During my PhD I made extensive use of both IDL and Python for data processing and analysis, primarily focused on high-resolution integral field spectroscopy. Since then I have worked with both languages with particular emphasis on the processing of large data sets from the Gaia mission and statistical analysis of wide-field imaging surveys of nearby galaxies.
In 2019/2020 I have been developing my skills in Java, C#, and C++ and have been working on a number of independent projects, including developing games with the Unity and Unreal 4 game engines. Some of these projects are shown on my projects page.