Hello, world!

Hi everyone! Welcome to my blog!

My opinion on blogging to paraphrase Winston Churchill - “Never have so many, written so much, read by so few.”

So why on Earth have I started a blog?

I make a lot of notes and often find myself referring back to these including programming commands etc. I figured I will store them here in a centralised place & open-source them.

To see why I’ve started a blog it makes sense to look at who I’ve started a blog for:

  1. You - To provide as much value as I can to you, the reader
  2. Me - To help organise my thoughts, retain the things I learn & improve my writing
  3. The world - To help actually improve it by using reason and taking action, not just by good intentions alone. Ambitious I know 😅

Who am I?

I am a bioinformatician and PhD student at the University of Cambridge

What will I write about

I hope to start blogging more frequently about (my) research and PhD-related things to document stuff that I learn. I’ll likely cover topics such as:

  • Biology
    • Immunology
    • Vaccines
    • Viruses
  • Computing
    • Bioinformatics
    • Data Science
    • Machine learning
  • Maths
    • Statistics
    • Probability theory
    • Linear algebra

As time goes on I may expand to cover other interests. These may include effective altruism, tech (start-ups), personal development, productivity, life learnings, reading, travel, health and relationships.

Thank you

I don’t really anticipate anyone else reading this blog so I’m flattered if you are 🙂

If you’re interested in any of the topics above then you’re in the right place. I will generally try and keep my posts short, fun & practical. I would love any feedback you might have so please don’t hesitate to reach out.

Disclaimer: Many of the blog posts will likely not be as throughly researched and well presented as I would like. This is in the interest of time in order to publish more content.

Thanks for reading!

Phil Palmer
Bioinformatician PhD Student

My research interests include bioinformatics, machine learning and viral genomics.