- Reading time: 3 minutes
- Price: Free download
- Published: 17th September 2026
- Word count: 633 words
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Personal statement example
My interest in cosmology became concrete in my third year, when a lecture course on general relativity turned the Friedmann equations from something I had read about into something I could actually manipulate. I remember being struck that two lines of algebra, given an assumption about the contents of the universe, predict how distances grow with time. That combination of sparse mathematics and testable consequences is what I want to work on for longer than a single term.
My final-year project gave me a first taste of doing that properly. I used a publicly released compilation of Type Ia supernova distance moduli to fit a flat cosmological model, treating the matter density and the Hubble constant as free parameters. I wrote the likelihood and a basic Metropolis-Hastings sampler in Python rather than using an existing package, partly because my supervisor suggested it and partly because I wanted to understand what the sampler was actually doing. The result was unremarkable in the sense that it agreed, within generous error bars, with values I could have looked up. What I gained was less tidy and more useful: an appreciation of how much the answer depends on the treatment of nuisance parameters, and a healthy respect for the difference between a chain that has converged and one that merely looks smooth. I spent a fortnight debugging a problem that turned out to be my own poor choice of step size, and I now check trace plots before I trust anything.
Alongside the project I took a computational physics module in which I worked with one other student on a shared task: simulating structure formation in a very simplified one-dimensional model and comparing the growth of density perturbations with the linear prediction. We split the work so that she handled the integrator and I handled the initial conditions and analysis, then swapped code to check each other's assumptions. It was a small piece of work, but it taught me how quickly two people can diverge in their definitions if they do not agree notation early, and how much time a shared set of test cases saves.
Outside my degree I have supervised evening shifts in a supermarket since my second year, which has meant handling rotas, stock problems and occasionally difficult customers while keeping a team of six moving. It is not astronomy, but it has made me better at explaining things calmly and at finishing tasks that are not intrinsically interesting. I also help at public observing evenings run by a local astronomical society, usually queue-managing at the telescope and answering the same few questions about why we cannot see the flag on the Moon. Explaining redshift to a curious eleven-year-old without using the word metric is a genuinely instructive exercise, and it has sharpened my sense of which parts of my own understanding are secure.
My reading has been steady rather than exhaustive. Working through parts of Ryden's Introduction to Cosmology filled gaps my lecture notes left, particularly on the thermal history of the early universe, and I have made a slower start on Dodelson's treatment of perturbation theory, which I expect a master's course to put on firmer ground. The topics I most want to study are the physics of the cosmic microwave background and the statistics used to extract parameters from large surveys, since that is where my computational interests and my theoretical ones meet.
I am applying for taught postgraduate study because I want the formal grounding in perturbation theory and statistical inference that a one-year project could only gesture at, and because I would like to test whether research is the right longer path for me. I am prepared for the step up in pace and happy to be told when my methods are sloppy.
Why this example works — strengths and ways to improve
This is a strong, honest taught-master's statement. Your project paragraph stands out because it reports an unremarkable result and then explains what you learned about nuisance parameters and convergence. The reading and aims are realistic. The main gaps are thin evidence of wider academic preparation beyond one lecture course, and a closing that could state your intended direction more precisely.
Subject motivation
two lines of algebra, given an assumption about the contents of the universe
Your motivation is anchored in a specific intellectual moment, not a childhood fascination. Linking the Friedmann equations to testable predictions explains why cosmology appeals to you: sparse mathematics with observable consequences. This is convincing, though one sentence on how the interest developed after that lecture would strengthen it.
Academic preparation
a lecture course on general relativity
General relativity, computational physics and the final-year project show relevant groundwork. You say little about your wider mathematical or statistical training, such as probability, linear algebra or field theory. For an inference-heavy master's, briefly noting the coursework that supports your stated interests would make your readiness clearer.
Evidence and reflection
the difference between a chain that has converged and one that merely looks smooth
This is real methodological reflection, not a generic skill claim. Writing your own sampler, admitting the step-size error and changing your practice to check trace plots shows critical habits suited to advanced study. Your candour about the unremarkable result strengthens credibility rather than weakening it.
Relevant experience
swapped code to check each other's assumptions
The paired simulation shows collaborative verification and a lesson about agreeing notation early, which is directly useful in research. The supermarket and outreach paragraphs earn their place because you draw specific lessons from them. The eleven-year-old example is the most persuasive. The rota details matter less.
Credibility and voice
My reading has been steady rather than exhaustive.
Your voice is measured and plausible for a final-year undergraduate. You do not overclaim: Dodelson is a slower start, and the project result is modest. This restraint builds trust. Take care that the self-deprecation does not tip into underselling, especially in the final sentence.
Structure and format
happy to be told when my methods are sloppy
The structure moves logically through motivation, project, collaboration, wider experience, reading and aims, and the prose is economical. The closing line is likeable but ends on willingness to be corrected rather than on purpose. A final sentence connecting your CMB and inference interests to your next step would conclude more firmly.
What you’ve done well
- The supernova project paragraph shows genuine methodological understanding: nuisance parameters, convergence diagnostics and a concrete debugging lesson.
- Non-academic experiences are tied to specific, transferable insights rather than listed as generic skills.
- Your aims are realistic and coherent, framing the master's as grounding and a test of research fit.
How this draft could improve
- Briefly name the mathematical or statistical coursework that prepares you for perturbation theory and inference.
- Trim the supermarket logistics so the space goes to the explanation skills you draw from it.
- Replace or extend the final sentence so the statement ends on your intended direction, not only on openness to criticism.