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I have developed different relevant skills in the field of data science, specifically using deep learning and evolutionary computing frameworks such as TensorFlow, Keras and genetic algorithms methodology. I am a daily user of Python and R languages, Linux operating systems and HPC services to train and evaluate my computational models.
I started my PhD in neuroscience and artificial intelligence intersection. I decided to test the biological hypothesis in which astrocyte elements are key in neural transmission information, through a in silico framework. For this purpose, I am developing artificial neural-astrocyte networks topologies to solve several realistic problems. Theorical results also are tested through in vivo models to define new neuroscience mechanisms.
Since December 2019 I am funding by a competitive fellowship to undertake my PhD. In addition, I have been teaching staff during the last three academical courses at department of Computer Science and Information Technologies.