PhD Speed Date
Last week my two supervisors were very busy. One away on a tour of Europe (or something of the like) and the other away at a conference in another state, taking most of the lab with him. As I ended up being quite alone with no one to bounce ideas off from I asked one of my supervisors to set me up with someone to talk to. My supervisor pulled through and my week ended up being filled up with several meetings with my supervisor's students. Here I learned a bunch of fascinating new maths as well as life after being an undergraduate at MIT.
The group I met with were all working for my supervisor meaning the overarching theme with their work which was applied computational mathematics, with a leaning to biology. Standing out to me was the work of Vishal, a PhD student from Birmingham, who built simulations to explain the age-old question of why do you get 3+ pieces when you snap spaghetti. He also investigated why some knots hold more securely than others. In order to investigate these problems, Vishal worked with experimentalists to get data that explored a range of inputs, e.g. rotation of spaghetti when being snapped. The maths in all of this is in using the data collected to build a model that fits. A large issue that the people I spoke to seemed to face is deciding how much parameters is the right amount for your model. Not enough parameters might mean you end up compromising on accuracy but too many and it gets too complicated. Yes, there is such a thing as too complicated for a PhD student at MIT (reassuringly.) In the end, people settled with the best amount of parameters they could manage but were always looking to add some more. Parameters seem to only be the start of their problems however as other issues such as waiting for data from experimentalists and getting stuck somewhere. These problems have great solutions. Most of the people I spoke with had multiple projects on the go to protect themselves from wasting time when they can't make progress. Multiple projects also mean more papers to your name, and if your supervisor is nice you'll get a place high up on the author's list.
Most of the meetings I had took place in the newly refurbished maths common room, complete with places to work, a beautiful view of the Charles River and of course a blackboard in every corner, a location where students of all stages of their academic journey feel comfortable to sit and chat. Not only did we discuss work we discussed life as a postgraduate. In terms of competition, there seems to be none of it here. Of course to some, there seems like times where others may seem to be working much harder than you are but the key seems to be happy with where you are and where your work will be able to take you. There is a community feel where people are happy to share ideas with one another. Some here were looking forward to their future with MIT having just started, while others were thinking about where to apply for a post-graduate position and how difficult it may end up being. Another PhD student, Boya, told me that she decided that a PhD was for her when an internship went seriously wrong, while others claimed they always saw themselves going into further studies. Of course, research is just one aspect of the work that this group are required to do. Being multi-talented these students must lead projects, teach and present their work to many different groups of people.
By the end of the week not only had I heard from 6 very kind people but I had a new project to think about to. Nico another PhD student challenged me to work on a stochastic knot simulator on Julia alongside my current work which I proving to be fun (but with lots of Physics.) Even if my day-in-day-out work here wasn't enough to give me an insight into the life of one in research, speaking to these post-grads gave me an even deeper understanding. I doubt any of the people I met will end up stumbling upon this blog but if they do I'd like to give them a massive thank you.
Bonus Content: What did I speak to each person about?
23/07/19
Nico:
The group I met with were all working for my supervisor meaning the overarching theme with their work which was applied computational mathematics, with a leaning to biology. Standing out to me was the work of Vishal, a PhD student from Birmingham, who built simulations to explain the age-old question of why do you get 3+ pieces when you snap spaghetti. He also investigated why some knots hold more securely than others. In order to investigate these problems, Vishal worked with experimentalists to get data that explored a range of inputs, e.g. rotation of spaghetti when being snapped. The maths in all of this is in using the data collected to build a model that fits. A large issue that the people I spoke to seemed to face is deciding how much parameters is the right amount for your model. Not enough parameters might mean you end up compromising on accuracy but too many and it gets too complicated. Yes, there is such a thing as too complicated for a PhD student at MIT (reassuringly.) In the end, people settled with the best amount of parameters they could manage but were always looking to add some more. Parameters seem to only be the start of their problems however as other issues such as waiting for data from experimentalists and getting stuck somewhere. These problems have great solutions. Most of the people I spoke with had multiple projects on the go to protect themselves from wasting time when they can't make progress. Multiple projects also mean more papers to your name, and if your supervisor is nice you'll get a place high up on the author's list.
Most of the meetings I had took place in the newly refurbished maths common room, complete with places to work, a beautiful view of the Charles River and of course a blackboard in every corner, a location where students of all stages of their academic journey feel comfortable to sit and chat. Not only did we discuss work we discussed life as a postgraduate. In terms of competition, there seems to be none of it here. Of course to some, there seems like times where others may seem to be working much harder than you are but the key seems to be happy with where you are and where your work will be able to take you. There is a community feel where people are happy to share ideas with one another. Some here were looking forward to their future with MIT having just started, while others were thinking about where to apply for a post-graduate position and how difficult it may end up being. Another PhD student, Boya, told me that she decided that a PhD was for her when an internship went seriously wrong, while others claimed they always saw themselves going into further studies. Of course, research is just one aspect of the work that this group are required to do. Being multi-talented these students must lead projects, teach and present their work to many different groups of people.
By the end of the week not only had I heard from 6 very kind people but I had a new project to think about to. Nico another PhD student challenged me to work on a stochastic knot simulator on Julia alongside my current work which I proving to be fun (but with lots of Physics.) Even if my day-in-day-out work here wasn't enough to give me an insight into the life of one in research, speaking to these post-grads gave me an even deeper understanding. I doubt any of the people I met will end up stumbling upon this blog but if they do I'd like to give them a massive thank you.
Bonus Content: What did I speak to each person about?
23/07/19
Nico:
- Looking at how long polymers/nodes connected with strings behave in fluids. Essentially nodes with forces from other nodes as well as random noise from fluid's needs to be modelled to understand how such polymers might knot. This is the purpose of the Stochastic Knot Simulator.
Alex
- Speaking about the surface of cells and how reactions in cells create mechanical reactions causing more chemical reactions that must be solved with differential equations. The mechanical reactions also cause some surface distortion causing an overlap in geometric mechanics.
- Modelling of the swirling of bull sperm cells at different temperatures. Explaining how the cells are tracked by a computer and then put into a model that helps to further model what happens at a macroscopic level.
Boya
- Looking at Biofilm on a 3-D level and how bacteria with different inter-molecular forces align. Bacteria behave in certain ways to show that the Biofilm was about to form, such as rafting. These are simulated and modelled.
Dominic
- Modelling elastic biofilms travelling with a flow where the film shows a slight deformation when the flow stops.
24/07/19
Henrick
- Discussing parameter estimation in Julia for ODE's, simulating the movement of bacteria from the centre of a petri-dish.
- Using optimisation in order to find variations in the thickness of wiring to decrease output fluctuation of wind farms. This was fascinating as the model ended up looking like vein branches.
- Discussing topological insulators and Vanderpol insulators that carry energy around a boundary if rotating.
Pearson
- Discussing cell movement on a circular petri dish, using an oDE to simulate characteristics of cells such as velocity.
- An investigation into how waves on a starfish eggs affect patterns on the starfish.