Data Scientist familiar with gathering, cleaning and organizing data for use by technical and non-technical personnel. Advanced understanding of statistical, algebraic and other analytical techniques. Highly organized, motivated and diligent with significant background in Mathematics, Scientific Research, Programming Languages, Probability and Statistics, Machine Learning/Deep Learning and also Software Development and Team Leadership and Management.
Responsible for building advanced analytic (ML/AI/Optimization) algorithms within a Data Science program and working with Business Partners and Friends of Data Science to insert algorithms into business processes and activate them directly with the business.
Research Proposal: Computational modeling and simulation of epidemic infectious diseases
Research Project: Visualization and Analysis for Seismic Interpretation
Disciplines:
Objectives:
Disciplines:
Objectives:
Machine learning
undefinedHPC simulations applied to wind and biomass energy production and geophysics exploration - HPC4E. Feb 2016 - July 2018
The HPC4E project aims to apply the new exascale HPC techniques to energy industry simulations, customizing them, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources: wind energy production and design, efficient combustion systems for biomass-derived fuels (biogas), and exploration geophysics for hydrocarbon reservoirs.
Biological System Simulator (BioSyS). Sep 2003 - Aug 2010
BioSyS is a software that facilitates the study of biological systems that are described by Ordinary Differential Equations (ODEs). This software is designed to be capable of performing distributed simulations using Grid computing, stores the results in a database, and allows further studies, incorporating various types of analysis such as charts, dynamics population, algorithms of clustering, classification, user-defined rules, stability, and bifurcations, using data mining techniques. BioSyS 1.0 makes it easier for researchers with a number of tools and algorithms that allow them to carry out investigations in an easier way.
E-science grid facility for Europe and Latin America 2 - EELA-2. Jan 2008 - Jan 2010
The EELA (E-infrastructure shared between Europe and Latin America) project aims at establishing a bridge between the existing e-Infrastructures in Europe and those emerging in Latin America, through the creation of an interoperable Grid Infrastructure - based on the RedCLARA and GÉANT networks - for the development and deployment of advanced applications in Biomedicine, High Energy Physics, e-Education and Climate. EELA is expected to help reducing the digital divide in Latin-America, making available to researchers a high performance e-Infrastructure for advanced investigations, later extendable to a larger community of users.