Juan García Sánchez defends his PhD: "It's a privilege to have people around to ask for advice"

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Juan García defended his PhD thesis at the Materials Science Insitute of Madrid (ICMM-CSIC) on September, 18 at Salón de Actos. Entitled 'Development of a platform for the analysis of the nanomechanical response of cells: theory, simulations, and applications', the thesis has been directed by Ricardo García. The young researcher explains here his work: 

Why did you choose ICMM for your PhD?
In my faculty of Physics, in Salamanca, I looked at the bulletin board while waiting for some friends, and I found the announcement of a job offer in nanotechnology. I have always been interested in this field; in fact, my TFG and first TFM were both about systems at these scales.
At first, I was hesitant to apply because of the drastic change of location, but at home my family supported me to do so. Therefore, by choosing to do my PhD here, it was not only a reaffirmation of my interest in this field within an institution specialized in it, but also an opportunity to leave my comfort area and live new experiences.

How would you explain your research to a non-scientific audience?
In science, in order to know how a system works at the mechanical level, tools with which you can control the pressure exerted on it, and record its reaction, are typically used. When the system is as small and fragile as a cell, the tool must also be small and especially sensitive to these reactions. When, in addition, you have cells of all kinds of sizes, shapes and behaviors, you need to record a lot of these reactions from many different cells to get to understand why they behave the way they do.
To cope for this huge amount of data, my main job was to create a program that could take it and get results with the least effort and time required from the user. The program contains, on the one hand, calculation strategies to clean these data from reactions other than those from cells, and on the other, mathematical models which to compare these reactions with. These models are nothing more than tabulated reactions of very specific types of materials, and the comparison is to check which type the cell reaction most resembles, and assign numbers to the characteristics of these reactions. These numbers, properly organized, are what allow us to unravel the details of cells’ behavior against the conditions to which they are subjected.
On the other hand, in order for these models not to be too specific, corrections are added that better follow characteristics of the cell's environment. To prove that, the models are faced with controlled recreations of simplified real systems, that is, simulations. These simulations are generated by more general mathematics that can roughly solve the behaviors that the models try to represent. Thus, they are used as an important visual basis for such verification, and for more features to be taken into account in the future.
As the icing on the cake, during this work I was able to detect some patterns within this data that could complement independently the managed models.

What are the main applications of your research? Could you give us an example?
To begin with, the developed program, cForce, is designed to be used on any set of measurements of two experimental techniques of the Atomic Force Microscope, the so-called Force – Distance curves and nanorheology. The program is conceived as free software, so the idea is that any other group or individual can benefit from the analysis of their data from thanks to these techniques and accelerate experimental research.
On the other hand, the energy analysis of these measurements offers new channels of direct information about the samples, which can support the interpretation of their behavior. These calculations do not depend on specific models, so a specific type of behavior is not assumed when analysing the results, and they are much faster too.
In addition, the reinterpretation proposal in one of the most used mechanical models lately aims to improve the understanding of its parameters, and therefore the interpretation of its results.

What are the lessons you have learned here? which one do you value the most?
The importance of having a good basis to start with a task, the privilege of having people around with more experience than you to ask for advice, and that it is better to check documentation and the technical service of a software before being blindfolded. I could name other lessons at a technical level from what I have done during the thesis, but I know that these will serve me much more at a general level for the future.

How do you think this experience will contribute to your training and to your future?
I have already named the previous lessons, which will surely serve me for the next jobs and teams in which I will get involved. Apart from these, I have gained a lot of experience in programming, developing mathematics on my own, and working in the laboratory. This has been a very useful first work experience, halfway with the academic world. It has allowed me to experience how things are done in the research world, and it has also given me many opportunities to interact with people from other backgrounds within it.

What are your plans once you finish your PhD?
For the time being, I will exploit the knowledge and experience in programming that I have gained in these years, and I will pause my research career. I do not intend to disassociate myself completely from research, as I will continue to pay attention to the news of the research lines I am interested in, but for the moment it is the path that I best consider to continue. Maybe in the future I will return, with much more experience to make better programs and better contributions to science. I would like that to happen.

Why did you become a scientist? Who have been your role models?
Since childhood, I wanted to know and understand how the world that surrounds me works, I was a lot to ask about things at medical consultations. I would say that this natural curiosity has inevitably led me down this path since school. I wanted to know what was known about reality, and have the opportunity to contribute to this building of science. That is why I have many reference models in the mathematicians and physicists who came before to develop the theories that we handle naturally today. However, if I had to highlight some, I would name Hertz and Maxwell on the one hand, and Planck and Boltzmann on the other. Of course, I am not forgetting about scientific divulgation, because it was a book by Brian Greene, lent by a good friend, that ended up expanding my vision of physics and the universe.