Research Guidance

Define a specific problem, explain why it matters, and connect it to a clear research gap. State focused questions or objectives, justify the proposed method, identify expected contributions, and provide a realistic timeline. Treat the proposal as a reasoned plan rather than a promise that every detail will remain unchanged.

Look for alignment between your proposed topic and the supervisor’s recent publications, active projects and methods. Read several of their papers before making contact. Explain the connection briefly, show what you can contribute, and ask whether they are open to discussing supervision rather than sending a generic request.

Use a specific subject line and keep the message concise. Introduce yourself, state your research interest, explain why you are contacting that person, and identify the relevant experience or idea you bring. Attach only essential documents and close with one clear, courteous request.

Send a short agenda or progress note beforehand. Report evidence of progress—results, analysis, decisions or written material—rather than only listing activities. Record agreed actions, responsibilities and dates after the meeting, then use them to organise the next period of work.

Break the project into measurable outputs such as a protocol, dataset, analysis, chapter or manuscript. Track dependencies, risks and decision points, and review the plan regularly with your supervisory team. Allow time for equipment problems, ethics processes, revision and unexpected findings.

Define the review question and search boundaries before collecting papers. Document databases, search strings, screening rules and dates. Critically compare evidence, methods and limitations instead of summarising sources one by one, then show how the synthesis establishes the need for your study.

Use consistent filenames, version control and a documented folder structure. Keep raw data unchanged, separate it from processed data, record units and instrument settings, and maintain a data dictionary. Store secure backups in approved locations and follow institutional ethics and retention requirements.

Use AI to support discovery, organisation, coding or language refinement—not to replace scholarly judgement. Verify every factual claim and citation against the original source, protect confidential information, preserve an audit trail where required, and follow university, journal and funder policies.

Group comments into scientific, structural and editorial issues. Address each point directly, explain the change made, and justify any recommendation you do not adopt. Keep responses professional and evidence-based, even when feedback is difficult or contradictory.

Begin with a tractable question, a transparent working system and regular writing. Build competence in research design, evidence appraisal, data management and communication before chasing complex tools. Seek feedback early, document decisions and create small, reproducible outputs that demonstrate progress.