Applicants will be expected to work with a diverse set of data sources, such as time series data, spatial and graph data, and semi-structured and unstructured data, in order to build statistical/machine learning models to uncover and generate value-driven insights. Xerox has a wide range of data sets that can be used in the research problem.
Knowledge of fundamentals of machine learning, data mining, and statistical modeling is highly desired. Proficiency in publicly available data analytics toolkits (such as R, WEKA, MALLET, etc.). The applicant should also have strong skills in explaining and interpreting the analytic models and outcomes in both research and application contexts.
Role/Responsibilities
Invent, design and prototype novel next-generation technologies in the areas of machine learning, data mining, and statistical modeling. Collaborate closely with other R&D scientists and engineers in a multi-disciplinary work environment. Areas of particular interest are feature selection, feature representation, deep learning, time series analysis, graph analysis and data visualization.
Qualifications
• Enrolled in a Ph.D. program in computer-science program or related field in data science. Work experience, and with a strong record of scholarship or entrepreneurship a plus. Candidates in the latter part of a PhD. Program are preferred.
• Strong knowledge and skills in rapid prototype programming languages, such as Python, Java, and/or R.
• Candidates should possess the interest to work in multi-disciplinary environments, and should have the desire to see their ideas realized in practice.
• Strong analytical, written and verbal communication skills.
If you are interested, please send your resume to arvind.agarwal@xerox.com
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