There was nothing else to assume regarding that hole in front of Feynman's grave, other than it is a designated cupholder for coffee.  

Maria Kalimeri, PhD
Data Scientist, Researcher, Biophysicist

@ Nightingale Health Ltd.
Mannerheimintie 164a
00300 Helsinki
Finland
e-mail: maria.kalimeri [at] nightingalehealth.com
             mkalime [at] gmail.com 
github: https://github.com/mkalime


Hi there,  

I am a data scientist and a researcher. I work in the science team of Nightingale Health Ltd., a biotech company based in Helsinki that specializes in blood biomarker analysis. Nightingale's platform combines a high throughput NMR (Nuclear Magnetic Resonance) spectroscopy with a sophisticated data analysis in order to quantify more than 220 blood biomarkers from a single sample. Such detailed biological data can help predict or improve current predictions of the risk for chronic diseases, such as cardiovascular disease and diabetes. 
 
In parallel, I have been studying protein and lipid dynamics via biomolecular simulations. Specifically, since 2014 till recently, I worked as a post-doc in the group of Ilpo Vattulainen in Tampere University of Technology, focusing on the structure and dynamics of actin-binding proteins and their interaction with cell membranes. See here a press release on a recent article on the different membrane affinities of actin-binding domains.

Previously, I conducted my doctoral research, under the supervision of Fabio Sterpone in Laboratoire de Biochimie Théorique (Paris, France), on the correlation between protein thermal stability and mechanical flexibility. In an effort to describe protein flexibility, apart from protein models of different resolution, we used novel complex network and machine learning approaches for the analysis of protein energy landscapes. For more details, please, have a look.

Except for simulation techniques and protein stability and dynamics, other scientific areas that I find very attractive are information and graph theory, mostly on their application side, as well as quantitative and computational linguistics. During my undergraduate thesis, I also worked on the extraction and analysis of statistical patterns from time series generated by somewhat-bigger-than-proteins systems, like seismic faults and the Earth's magnetosphere. The aim there was to find reliable precursors for catastrophic events like earthquakes and magnetic storms, respectively.