Maths and Physics bring me great enjoyment, and I would like to study these subjects at the highest possible levels. I enjoy playing with ideas, and the calm happiness that thinking and solving problems brings me. It would be an anchor in my life to study physics, something which I can pivot around to explore the world. I am dyspraxic and this is both a blessing and some difficulty. As a result, I have had to develop stronger than usual work ethic and organizational skills. I believe the difficulty comes with the benefit of unconventional thinking. As such, I appreciate the creativity and elegance in solutions to problems such as Bernoulli's solution to the brachistochrone. I enjoy solving mathematical and physical problems in unconventional ways. I love to draw and drawing offers me a way to explore and visualize ideas. I am interested in animations and digital design. I taught myself programming in Python, C++, Haskell, and MATLAB. I have used these skills to program physics, including a study on gravity, simulation of planetary motions, springs, soft body simulations, cloth simulation, fluid simulations, and the simulation of particles and turbulence. I also played with programming neural networks. Neural networks came to my notice when I read that after a mere 4 hours of learning, Google’s Alphazero AI thrashed the previous best chess engine, Stockfish, in a 100 game match without a single loss! I am a keen chess player, having played for the school team, so hearing about this inspired me to look further and create a neural network of my own. During the Summer of 2018, I spent a month at the Laboratory of Molecular Biophysics at Uppsala University in Sweden where I worked with Drs. Filipe Maia and Tomas Ekeberg on image reconstruction algorithms in Python. I enjoy skateboarding and riding BMX. I have been teaching myself the guitar, piano and mandolin as well as juggling. This gap year is allowing me a glimpse of science outside the classroom. Currently I am employed as a Research Assistant at the European Extreme Light Infrastructure (ELI) in Prague where I am learning about photon science. I have the opportunity to deepen my knowledge about lasers and their applications, experimental techniques and design. I will be applying mathematical modeling in experimental design and data analysis, concerning ionization and molecules in intense laser pulses. In addition I will be developing algorithms to sort large amounts of data. I hope to spend this gap year constructively. I am adapting to life away from home and learning about science, Czech culture and beer. In the spring and summer I intend to refresh and develop my Hungarian and German language skills.
이것은 기존 UCAS 형식으로 작성된 성공적인 자기소개서입니다. 2026학년도 입학부터 자기소개서는 세 개의 개별 답변으로 바뀝니다. 아래는 각 질문에 대한 우수한 답변이 어떤 모습인지 보여주는 예시 — 경제학 — 입니다:
Volunteering at a Saturday food bank in Croydon, I helped a single father of three who had moved into temporary accommodation after a zero-hours contract collapsed. What startled me was not the hardship but the bureaucracy — he had been waiting six weeks for Universal Credit because a payment glitch had reclassified him as self-employed. A Sutton Trust talk by Stephen Machin pushed me from that observation toward the literature on benefit take-up and conditional cash transfers — first Banerjee and Duflo's evidence from rural India and Mexico, then Anna Aizer's recent NBER work on the design of welfare-to-work programmes in the US. I want to study Economics because the question running through these readings — why some welfare systems escape the dependency trap while others reproduce it — has rigorous answers that combine empirical microeconomics, mechanism design, and political economy in a way no other discipline can.
Further Mathematics has been the single qualification that has reshaped how I read Economics. Working through the chapter on differential equations let me approach Solow's original 1956 paper rather than the textbook simplification — and seeing convergence as an asymptotic result rather than a guarantee made me sceptical of growth-theory papers that quote "China is converging to the US frontier" without specifying the underlying production-function assumptions. That scepticism became my EPQ. Building on Acemoglu and Robinson's Why Nations Fail and Elhanan Helpman's The Mystery of Economic Growth, I asked why the post-1978 Chinese growth episode fits neither the standard Solow convergence prediction nor the institutional pessimism of the extractive-institutions framework. My answer, framed around within-country variation in property-rights protection across coastal special economic zones, was the most rigorous piece of academic work I have produced. Economics A-level supplied the discipline-level vocabulary — perfect competition, Pareto efficiency, deadweight loss — but the model that has stayed with me is the prisoner's dilemma I first met in Maths Olympiad preparation, which I returned to repeatedly when reading Schelling's The Strategy of Conflict. In History A-level, the unit on the Bretton Woods system gave me the institutional context for Friedman's 1953 essay on flexible exchange rates — a connection that taught me how economic theory and political choice constantly co-evolve.
For the John Locke Institute 2025 Economics paper I argued — against my initial intuition — that personalised pricing is welfare-improving in aggregate, drawing on Pigou's first-degree price-discrimination framework, Hal Varian's 1989 paper on price discrimination, and the more recent empirical work by Dubé and Misra on ZipRecruiter's pricing experiments. Writing the essay forced me to take seriously the strongest version of the fairness objection — Sandel's argument in What Money Can't Buy that markets reshape the goods they price — and then to build a synthesis that conceded the moral worry while defending the consumer-surplus calculation. I came out of the process convinced that the welfare economics taught at undergraduate level is more subtle than the textbook indifference curves let on. Outside the essay competition, the book that has shaped me most is Katharina Pistor's The Code of Capital. Pistor's argument that property law constructs rather than merely protects economic value runs counter to the standard market-design literature I had been reading, and I have spent two terms working through her chapters on collateral, debt, and shareholder rights alongside the Acemoglu-Johnson critique she draws on. To test the framework against my own context, I built a small dataset on Hong Kong residential property using the publicly released Land Registry data and computed the share of the housing stock held by corporate (rather than personal) entities — a 32-line Python project that taught me more about institutional economics than any chapter I had read on it.
세 답변 합계 최대 4,000자, 각 답변 최소 350자입니다. UCAS 공식 안내를 참조하세요.