It’s fair to say, that I am currently in a state of flux. At the beginning of June I submitted my thesis as well as starting an MRC Skills Development Fellowship, beginning the next step of my research career. Consequently, the past few weeks my day-to-day activities have been rather varied, including preparing my Viva (like an interview but about your PhD research), starting the Fellowship (which comes with a fair amount of induction and administration), finalising a research paper based on a thesis chapter in the journal Epilepsia, presenting another thesis chapter at our weekly group meeting, and supervising an undergraduate student on a summer project.
Manoeuvring between these various types of activity is a new experience for me, and an interesting challenge, particularly since I imagine this is a bit more characteristic of the life of a Fellow or lecturer – not even daring to imagine the schedule of a professor!
The transition from PhD to Fellowship is somewhat eased by the fact that the Fellowship broadly builds on the research I undertook over the course of my PhD (which had the snappy title ‘Emergent Phenomena From Dynamic Network Models: Mathematical Analysis of EEG From People With IGE’), and so my Fellowship (‘Revealing the dynamic mechanisms of seizures: An integrated mathematical and clinical approach’) will incorporate many of the lessons I learned along the way.
The main idea behind the research is to develop mathematical models that enable us to discover new ways to improve the diagnosis of epilepsy. By developing tools and models from mathematics and combining these with clinical data collected by clinicians, we should hopefully be able to tell whether these methods provide a significant improvement to the accuracy of current diagnosis methods.
Even though the data needed for our methods is relatively easy to collect and the mathematical tools and techniques are relatively computationally inexpensive, the real clinical contribution of our methods crucially depends on its performance with people with epilepsy compared to those without – fundamentally are our models able to reliably predict from EEGs those who have epilepsy and those who do not. In order to build up groups to study I am working with some clinical neuroscientists at King’s College London. Currently I am taking care of all the associated paperwork, which means working through documents and screenings with lots of chasing up of people… It’s somewhat tedious, but will be definitely worth it when eventually I can lay my hands on the data!
