All PhD students who are formal members of one of the NeSCoR partners are automatically enrolled in the program. The program is not open to individual applications. The courses are offered by the local Graduate Schools of the NeSCoR partners, and many of the courses are open to PhD students from other universities and institutes.
The duration of the program is three or four years full-time, though this may vary according to local rules and regulations. The program aims to support participants in developing into scientific researchers who can independently design, carry out and report high quality scientific communication research and who can function as full members of the scientific community. The aims are described in more detail below in terms of skills, knowledge, and attitudes.
- Write research proposals and applications.
- Initiate, design and conduct communication research programs
- Write scientific articles that can meet international peer reviewed evaluation.
- Present papers at international conferences.
- Work in a research team.
- Discuss the findings of others in a collegial way.
- Supervise young researchers.
- The strong belief that what is considered the truth may be false, and vice versa.
- Willingness to (re)consider arguments and conclusions in light of empirical results or valid counterargumentation.
- Willingness to structurally monitor research developments and innovations in the social sciences broadly.
- Willingness to share research arguments, findings and conclusions, including submitting reports to peer reviewed evaluation and communicating with the professional and public domain.
Knowledge of …
- The most important philosophical theories on (the meaning of) ‘science’.
- The most important communication theories and their strengths and weaknesses.
- Research designs in the social sciences and their applicability in specific circumstances.
- The most important data collection methods, their strengths and weaknesses, and their applicability in specific circumstances.
- The most important measurement techniques, their strengths and weaknesses, and their applicability in specific circumstances.
- The most important data analysis techniques, their strengths and weaknesses, and their applicability in specific circumstances