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Programme code: 3120

Regulations: RD 99/2011

Knowledge branch: Sciences

Organised by:Department of Statistics and Operations Research (UV) Department of Statistics and Applied Operations Research and Quality (UPV)

Management Centre:Postgraduate School

Participating Universities:UV General Study, Universitat Politècnica de València

Programme Coordinator:Dr. Rafael Martí Cunquero

Places available for new students:10 places

Aims: This doctoral programme has the general objective of training researchers in the fields of Statistics and Optimization, providing the knowledge, techniques and necessary tools to solve quantitative problems and facilitate decision-making in the different fields of application. The doctoral studies aim to provide specialisation within the most important fields of Statistics focusing, among others, on the following research lines: Bayesian Methods, Space-temporal Statistic Methods, Statistical Analysis of Images, Statistic Control of Quality, Experiment Design and Industrial Statistics, Multivariate Analysis and Data Mining, and Temporal Series Prediction. As for Optimization, the research lines are: Lineal and Discrete Optimisation, Metaheuristics, Routes and Localisation Problems, Sequencing Problems, Production Planning and Cutting and Packaging Problems.

Description: The Doctoral Studies “Statistics and Optimisation” started being taught within the frame of the Royal Decree 778/1998 and obtained a Quality Mention. The doctoral programme has been followed up within the framework of the Royal Decree 1393/2007 and has obtained the Mention towards the Excellence for the academic years from 2011-2012 to 2013-2014. The existence of a doctoral programme in Statistics and Optimisation was mainly prompted by the social need of the incorporation of well educated professionals with research competencies to develop new methods and adapt those existing to novel environments in companies, researching centres and public institutions. The increasing demand in the use of each time more sophisticated methods, particularly in fields such as science, economy, industry, and administration, demands from the university the training of experienced doctors able to interacting in multidisciplinary fields.

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