Master of Bio-informatics postgraduate personal statement example

Personal statement example

Halfway through my final-year project, I discovered that my results depended on a spreadsheet that had quietly changed my data. A colleague's gene list had been opened in Excel, and several gene names had been converted into dates. The error was small, but it taught me that in computational biology the path from raw data to conclusion needs as much care as the bench work behind it. I want to study bioinformatics at postgraduate level because I enjoy that path, and I want the formal training to build it properly.

I graduated with a 2:1 in Biomedical Science. Most of my degree was laboratory-based, covering molecular biology, genetics, immunology and an introductory statistics module that I found more interesting than I expected. For my dissertation I chose a computational project. I reanalysed a publicly available RNA-seq dataset comparing yeast grown at normal temperature with yeast after heat shock. Starting from count tables, I used R and the DESeq2 package to identify differentially expressed genes, then carried out a gene ontology enrichment analysis. Many of the strongly upregulated genes were chaperones and other known heat-shock genes, which reassured me that the pipeline was behaving sensibly. The more useful part of the project came from the less tidy questions. I learned why normalisation matters when libraries differ in size, why adjusted p-values are needed when thousands of genes are tested at once, and how much a fold-change threshold can change the length of a results table. My supervisor encouraged me to write the analysis as a script rather than a series of manual steps. That made my final report reproducible and helped me find the spreadsheet problem before it reached my conclusions.

Since graduating I have worked full-time as a laboratory assistant at a commercial food-testing laboratory. My job is routine but exacting. I log incoming samples, prepare them for microbiological testing and keep track of batches through the laboratory information system. I am not responsible for interpreting results, but I see every day how much depends on accurate sample records and consistent procedures. Last year I noticed that our weekly summary of turnaround times was being compiled by hand. With my manager's permission I wrote a short Python script that read the exported records and produced the same table in a few minutes. It is now used by the team, and building it showed me how much I enjoy turning a repetitive task into something reliable.

Outside work I have been working on the gaps I know I have. I completed an online introduction to Python, and I have been working through Rosalind problems, which move from simple string handling to problems such as finding motifs and translating sequences. They have made me more comfortable with algorithmic thinking, though I am aware that my mathematical background is weaker than that of applicants from computer science. I have started revising linear algebra and probability so that the more quantitative parts of a master's course do not take me by surprise.

I also coach a junior badminton session on Saturday mornings at my local leisure centre. Explaining footwork to ten-year-olds has little to do with genomics, but it has made me patient and clear when I explain something technical, and better at noticing when a plan is not working and changing it.

I would bring to postgraduate study a genuine biological grounding, practical experience with real datasets, and habits formed in a laboratory where errors in records matter. I hope to develop stronger skills in statistics, programming and sequence analysis, and I am particularly interested in transcriptomics and in how analyses can be made easier for others to check and repeat. In the longer term I would like to work in a research or applied setting where careful computational analysis helps biologists answer their questions.