Before I was a writer, I got a physics PhD and worked as a biologist

I started my career as a scientist, with a PhD in physics followed by a couple of post-docs in computational biology. I’ve now taken the sideways step from science to science writing—check out my book, Ageless: The new science of getting older without getting old.

I decided to make this slightly unusual leap between physics and biology because I wanted to work on ageing. Ageing is probably the most fascinating problem in contemporary science and, I believe, understanding it is the greatest humanitarian mission of our time. Ageing, and all the diseases it causes, is the single largest cause of human suffering in the modern world and, by treating the underlying ageing process, we could potentially prevent many of these diseases simultaneously. To find out more, read my book!


I worked as a post-doctoral researcher in the Luscombe Lab at the Francis Crick Institute in London, using machine learning techniques to try to make sense of genomic data and medical records. I used neural networks to try to model where proteins and nucleosomes bound to DNA, and random forests and penalised regression models to predict patient outcomes using medical records data.

I also worked as a post-doc in the Ch’ng Lab at King’s College London, analysing survival and imaging data in C. elegans to dissect how genes in their neurons detect food in the environment, altering their lifespan.


I completed a DPhil in condensed matter physics at Oxford University in 2011, supervised by Prof Stephen Blundell. (‘DPhil’ is what Oxford calls a PhD.) I used a technique called muon-spin relaxation, which uses particle accelerators to fire particles called muons into various different kinds of material, to understand more about their properties. I looked specifically at magnetism and superconductivity, focussing on novel magnetic materials such as molecular magnets.

You can find an accessible summary of my DPhil in three parts: read about muons, magnetism and µSR to get an overview of what I got up to, and how it worked. I have since changed fields to computational biology, though I often still talk about physics, and will happily show you my maglev train!


MµCalc is the software I wrote during my DPhil, a Python-based dipole field simulator designed for computation of sample properties based on muon stopping sites, including the use of a novel Bayesian algorithm which I developed. It is still in active use by my old group in Oxford and in several other groups around the world. It is fully open-source, so if you would like to use it or build upon it, check it out on GitHub!

Other tools

  • SymGen, a simple Web application created to generate multiplication tables for groups of symmetry elements.
  • FµFcalc, for interchanging bond lengths and oscillation frequencies in symmetric linear FµF.

Posters and presentations