The objective of this programme is to educate doctoral students of Data Analytics so that they attain broad general knowledge and attractive specialist competence in Business Intelligence, Analytics, and Data Science that meet market and academic demands.
Students in this programme have diverse backgrounds – including business, computer/information science, engineering, and applied mathematics/statistics. The programme forms an important part of the research in Computing at Dalarna University.
Computing
Computing is the subject that deals with how data is represented, processed, and communicated in computerized systems. It also addresses how software and hardware technologies are used and developed to create useful system solutions for individuals, organizations, or society.
Data Analytics
Data Analytics involves the collection, modeling, compilation, and interpretation of large volumes of data, as well as the underlying algorithms, methods, and techniques that support data-driven decisions and actions.
Learning Outcomes
There are mainly five 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 Data Analytics is designed for students who are seeking expertise across the entire data lifecycle, along with deep specialization in a specific learning outcome.
Structure of the programme
The doctoral journey is a collaborative process where the student, supported by the supervisory team, develops a personalized research plan aimed at achieving doctoral qualifications. While the general curriculum provides the framework, the student and supervisors jointly create an Individual Study Plan (ISP) at the program's outset. This ISP serves two key purposes: it outlines the student's specific research trajectory while establishing benchmarks to track academic 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 a relevant field. Additional prerequisites are listed in the general programme curriculum.
There is doctoral student positions related to specific research projects that are open for application throughout the year. These positions are advertised under Vacant Positions on the university website.
Supervisors and Students
The principal 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.
