The objective of this programme is to educate doctoral students of Microdata Analysis so that they attain broad general knowledge and attractive specialist competence in the fields of Business Intelligence, Analytics, and Data Science that meet market and academic demands.
Students in this programme have diverse backgrounds – for example, business, computer/information science, engineering, and applied mathematics/statistics. The programme forms part of the reserach in Data and Information Management.
Microdata Analysis
Microdata analysis is a multidisciplinary field of knowledge that deals with the collection, modelling, compilation and interpretation of large amounts of data, as well as underlying algorithms, methods and techniques. Microdata analysis encompasses several interacting sub-areas such as artificial intelligence, decision support systems, management of limited resources, data modelling, experimental design, focus groups, geographic information systems, visualisation, measurement techniques, optimisation, forecasting, simulation and statistical inference. The subject is normative and its aim is data-driven decisions and actions.
Learning Outcomes
The first part of the programme comprises the collection of data and requires knowledge and understanding of various measurement techniques as well as the design of experiments.
The second and third parts comprise data capture, data processing and data storage, and require knowledge and understanding of advanced database methods as well as comprehension of the importance of metadata.
The fourth part is the analysis, often in the form of mathematical modelling of data that requires skills in statistical modelling, forecasting methods, simulation techniques, visualisation and data mining.
The fifth part comprises decision-making and action that require an understanding of techniques such as benchmarking and counterfactual analysis as well as economic decision-making and the dissemination of information within organisations.
The Doctoral Programme in Microdata Analysis is for students who wish to acquire skills in all parts of the process as well as expertise in a specific area.
Structure of the programme
In essence, it is the student supported by the supervisory team who defines the plan, the aim of which is graduation as researcher. However, a general curriculum frames the plan and at the start of the programme, the student and the supervisory team develop an individual study plan that serves both to define the student's research activities and to monitor student progress.
How to apply
We look for prospective students who want to develop as researchers in an interdisciplinary environment. You should have skills in data management and analysis with the objective of creating business value. To be eligible, you must hold at least a one-year master's degree in the field. Additional prerequisites are listed in the general programme curriculum.
You can apply in two ways.
- In the spring semester, doctoral students are recruited who will commence their studies in the autumn semester. Positions are advertised under Vacant Positions on the university website.
- There may also be doctoral student positions in specific research projects that are open for application throughout the year. These positions are also advertised under Vacant Positions on the university website.
Supervisors and Students
The primary supervisors guide the student towards the successful completion of the programme, which concludes with a thesis publicly reviewed at the thesis defence. Each student is assigned a primary supervisor, who establishes the supervisory team. This team holds complementary competencies to optimise the student's research support throughout the programme.
