Successful supervision starts with an understanding of the role, responsibilities and expectations involved. The Higher Degree Research (HDR) supervisory team is responsible for supporting, mentoring and guiding HDR candidates throughout their entire HDR journey.
Principal Supervisor responsibilities
Principal Supervisors track the progress of the candidate and lead the supervisory team. The Principal Supervisor has final responsibility for the decisions made by the supervisory team. The Sub-Dean Graduate Studies should be consulted or advised on substantive matters effecting candidature.
The Principal Supervisor will lead the supervisory team and is generally the key contact for HDR candidates.
Key Principal Supervisor responsibilities include, but are not limited to:
- negotiating expected roles with Co-Supervisors in conjunction with the candidate
- coordinating the operations of the supervisory team to ensure the candidate is supported in all areas
- rigorously monitoring the candidate’s ongoing performance, discussing any inadequacies with the candidate and completing mandatory progress reports
- communicating any issues with the Faculty Sub-Dean Graduate Studies
- ensuring research is undertaken with the appropriate ethics and other approvals in place
- ensuring suitable resources and facilities are available to the candidate
- recommending suitable examiners to the Office of Research Services and Graduate Studies when required
- supporting the Co-Supervisors where needed, leading any inexperienced supervisors and contributing to their supervisory development and skills.
Further information
Refer to Section 2 HDR Policy - Responsibilities of supervisors and the Sub Dean (Graduate Studies)
Supervisory team responsibilities
All members of the supervisory team will contribute to providing guidance on matters such as:
- the nature of research
- the Data management plan
- the choice of the research topic
- the planning and execution of the research program
- ethical issues relating to the research
- methodological issues
- data analysis issues
- exploring solutions for unexpected problems which arise in the research.