I have a multidisciplinary education spanning the fields of Biochemistry (BSc), Bioinformatics (Msc), and Computational Biophysics (PhD) with ~9 years of research experience. Among the topics of my research I have worked mainly on biomedical signal analysis and on the used of advanced theoretical models (classical/quantum) to study large biomolecular systems on simulations that normally required high performance computing facilities. In the type of research I am usually involved it is also important to make a proficient use of statistical physics algorithms and tools, as well as the capacity to debug and code new methods and data analysis routines. Therefore, I have extensive scientific computing coding experience using languages like linux bash scripting and C/Matlab/R/Python (scipy, pandas,scikit). For more than a year now, I have been following the developments in data science, big data, and predictive analytics. Consequently I have embarked on an ambitious plan of self-education. In this regard, I have read data science books and I have completed a series of courses and certifications that cover machine learning, statistical inference and regression, text/data/process mining, data clustering, getting/cleaning/exploring data sets, and Big Data programming models (Hadoop, Pyspark). Furthermore, I have improved my skills in data reporting and visualization using R (Rpubs, Shiny-Apps) and Python (Ipython notebooks) as well as creating collaborative environments using virtual machines. Additionally I am also familiar through practice and certification with computer repairing and networking. In my free time, diving is my favorite thing to do. Playing my acoustic guitar comes second but is still great fun.

Postdoctoral Researcher @ From March 2014 to Present (1 year 9 months) Genoa Area, ItalyPosdoctoral Researcher @ From June 2012 to May 2013 (1 year) Trieste Area, ItalyPostdoctoral Researcher @ Project advisors: Prof. Giacinto Scoles and Prof. Alessandro Laio. Peptide design for nano-devices with biomedical applications. From October 2011 to April 2012 (7 months) Udine Area, ItalyPostdoctoral Researcher @ Project advisors: Prof. Federico Berti, Prof. Fabio Benedetti, and Prof. Alessandro Laio. Development of computational methodologies to design high affinity peptides for biosensor applications. From September 2009 to September 2011 (2 years 1 month) Trieste Area, Italy

Doctor of Philosophy (Ph.D.), Structural and Functional Genomics @ International School for Advanced Studies (SISSA) From 2005 to 2009 Master’s Degree, Bioinformatics @ Havana Medical UniversityBachelor’s Degree, Biochemistry @ Havana University Rolando Pablo Hong Enriquez is skilled in: Machine Learning, Data Science, Big Data, Data Mining, Data Visualization, Python, R, Apache Spark, Statistical Data Analysis, Computer Networking, Statistical Inference, Regression Analysis, University Teaching, Signal Analysis, Bioinformatics