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Education objectives

The Doctoral Program in Information Management aims to promote knowledge and innovation in Information Management, particularly in the research of its impact on wealth creation, improving the performance of organizations and the development of new methodologies and decision making tools.

It provides advanced training through research, contributing to the progress of knowledge and the training of researchers, university teachers and highly qualified professionals. The research may follow a more theoretical trend or be developed in an applied context, allowing the knowledge transfer from academia to society.

This Doctoral Program aims to provide advanced knowledge for highly qualified researchers, teachers, technical staff and managers.

This cycle of studies in Information Management is designed to include four areas:

  • Data Driven Marketing
  • Data Science
  • Geoinformatics
  • Information Systems

Applications - 2nd call for applications
To complete the application, the applicant must register in NOVA IMS' Applications Portal, fill the form, upload their Curriculum Vitae and a letter of intent, pay the application fee (€ 51), and submit the application in the end, from April 7th to May 13th, 2021. The selection process is based on the analysis of the applicant's academic and professional curriculum.

General characterization

DGES code



Speciality Area



Access to other programs


Tiago Oliveira

Opening date

September 2021



€3.000 (per year)


after working hours

Teaching language


Degree pre-requisites

The admission process is based on:

  • Final grade of the master's and/or the bachelor's degrees;
  • Analysis of the academic and scientific curriculum;
  • Analysis of the professional curriculum;
  • Interview.

This path is an option of

PhD in Information Management

Conditions of admittance

To enter the Doctoral Program, applicants must meet one of the requirements set out in national legislation:

  • Hold a Master's degree or equivalent, or a bachelor's degree, in which the number of credits is at least 240. In this case the final grade average must be at least 16 (out of 20);
  • Hold a degree and a relevant academic or scientific curriculum and which has been recognized and approved by the Academic Board that declares that the applicant is able to carry out this cycle of studies;

Applicants must show proficiency (spoken and written) in English.

Evaluation rules


1º year - Autumn semester
Code Name ECTS
300003 Research Seminar I 7.5
200163 Experimental Design 4.0
300032 Scale Development 5.0
300031 Machine Learning 7.5
300028 Advanced Topics Geographic Information Science 7.5
1º year - Spring semester
Code Name ECTS
300004 Research Seminar II 7.5
300029 Genetic Programming 7.5
300027 Theories of the Adoption and Impact of Technologies 7.5
300033 Theory testing with structural equation modelling 5.0
300035 Theory Development 5.0
300034 Advanced Topics in Geospatial Analysis 7.5
2º year - Autumn semester
Code Name ECTS
300005 Research Seminar III 10.0
300007 Thesis 140.0
3º year - Autumn semester
Code Name ECTS
300006 Thesis 140.0