PhD course guide2017 - 2018
The Graduate School advises PhD candidates to enrol in close consultation with their doctoral supervisor. This ensures that the selected courses and workshops fit the Training and Supervision Plan (TSP). At least 30 ECTS in the TSP should be dedicated to PhD training. Also ensure to consult our enrolment policy before enrolling.
Each description in the guide has an indication of the entry level.
- Introduction: No to limited knowledge of the subject is required.
- Intermediate: An operational understanding of the subject is required.
- Advanced: In-depth course and/or geared towards advanced PhD candidates.
Is the course full or did you miss the enrolment deadline? Always make sure to register for the reserve and notifications lists! We will then be able to notify you on available spots or new dates.
Courses for doctoral supervisors and daily advisors
Courses for beginning PhD candidates
- Cross-cultural awareness and communication
- Doing the literature review
- English academic writing for PhD candidates
- How to manage your PhD project
- How to survive your PhD
- Impostor syndrome
- Making your research proposal work for you
- Professionalism and integrity in research (mandatory for all Graduate School PhD candidates)
- Responsible research data management (RDM)
- Searching, finding and managing your literature
- Security for fieldworkers
- Self-presentation: presenting yourself and your research
- Toegankelijk schrijven over je onderzoek (Dutch)
- Your personal PhD work-life balance
Methodology courses and philosophy of science
- Brush up your research design
- Brush up your SPSS skills
- Comparing nations in quantitative studies
- Data analysis with R
- Data visualisation, web scraping, and text analysis in R
- Delphi technique for elicitation of experts’ judgments
- Digital research methods for textual data
- Ethnography and its varieties
- Great thinkers of the 20th century
- Introduction to participatory action research (PAR)
- Method of con/text analysis for interviews and other biographic data
- Multilevel modelling 1: an introduction
- Multilevel modelling 2: multilevel structural equation modelling (SEM)
- Multiple criteria analysis (MCA) for complex decision-making
- Necessary condition analysis (NCA)
- Open interviewing
- Philosophy of the social sciences and the humanities
- Qualitative coding with ATLAS.ti
- Qualitative comparative analysis (QCA)
- Qualitative data analysis (QDA)
- Research synthesis and meta-analysis