Guidelines for writing a PhD proposal Please use the PhD proposal template provided on Alfresco (do not use older proposals as a template as details might have changed): https://team.swisstph.ch/s/TrB0dISEQqKXr2BWq18EIw and be aware of the following: 1. The proposal should not exceed 15 pages (excluding references) 2. For the main text, use font size 11, and single spacing (references can be smaller). 3. Prior to submission to reviewers and the Research Commission, your supervisor must read and agree with the submission.
The proposal should include: Topic
Comments
Front page
Title of project; PhD subject; student’s name, e-mail address and address; first & second supervisor’s names, date of submission; Institution name & address; co-institution (if applicable); first & second supervisor’s titles, positions, departments, e-mail address
Contacts Acronyms/Abbreviations Table of contents Abstract Introduction and background Objectives and research aim
Research plan and methods
Maximum 400 words summarising introduction, background, objectives, methods, and relevance of thesis Explain what research question(s) you will be addressing and why it is important. Explain objectives, hypotheses, specific aims, and relevance/benefits of the thesis. Clearly describe rationales for each research question. It may be useful to structure this section according to the manuscripts that will come out of the thesis research. Describe in detail how you will answer your research question(s), by addressing the following aspects, as applicable: • Study type • Study population and inclusion/exclusion criteria • Sampling / recruitment plan • Exams / instruments / measurements • Statistical analysis plan, including when relevant: o Statement of the null and alternative hypotheses o Precise definition of all outcome and exposure (treatment) variables o Statistical method(s) that you plan to apply o Strategy to minimise confounding o Specification of effect modifiers or subgroups that you intend to analyse o Method to account for non-independence of data (clustering) o Strategy for handling missing data and loss to follow-up o Statistical software that you plan to use • Sample size calculation / justification Appendix - 79
