The ultimate goal of this project is to address different mathematical challenges that appear in modern

mathematical optimization and in their application to network design problems and data science. This project

deals with the integration of three important branches of operations research and applied mathematics: mathematical

optimization, network design and data science. The main goal is to enlarge the catalogue of available techniques

and tools of mathematical programming, machine learning and operations research, to address essential problems

associated with the management and design of large-scale complex networks and data science. The second goal of

this proposal is to make a significant advance on the modelling and solution aspects of a wide range of problems in

data science and moving ahead the frontiers on the instance sizes and level of integration considered in the

operational analysis of large-scale network. These two goals are intertwined and they have to be addressed jointly.

Our goals try to cover a wide spectrum of challenges in mathematical programming in general and more

specifically, connecting network design and data science areas that can be considered nowadays among those with

major projection in current operations research.

G1 Challenging large scale network design problems from optimization

G1.1 Advanced models in the design and optimization of large scale networks

G1.2 Advanced modes in the design of locational decisions

G2 Data science with optimization lens: Advanced models

G2.1 Mathematical programming and classification problems

G2.2. Pattern recognition and clustering

G3 Applications: Image Segmentation Electron Tomography.

The achievement of the goals described above will have a direct application in the technological development

in strategic areas of the information society with immediate consequences on distribution and transportation systems

and on the improvements of the methodologies of data science.

If you are interested in applying for MSCA-PF, please submit by email to Antonio.rodriguezchia@uca.es (no later than 30th of July 2024) the following documents:

1. CV (including complete contact details and list of publications, projects, etc., and describing academic achievements and research expertise, focusing on those aspects relevant in the context of the project).

2. Motivation letter (including information concerning your research and career interests and goals, project idea aligned with our research lines and how the candidate will contribute with his/her expertise in the project, and your interests in this call).