Pre-Doctoral Summer School - PDSS 2022
Prepararing international students for doctoral school admissions
Do you have a master's degree or are about to get one? Would you like to pursue a career in academia and research? Have you thought of studying for a PhD? This programme will help you improve your chances as a doctoral candidate, by helping you understand professional and academic research and training you in research methods. It will also help you prepare a research proposal to apply for admission to a doctoral school at a EUROSCI Network partner institution or elsewhere.
1. A scientist, a teacher or a policy advisor? Why would I need a doctoral degree? PhD career paths. Do I have what it takes to do a PhD? Am I smart enough? Do I have enough motivation? Do I have the support of my family and friends? How much does a PhD cost? Can I afford it? Fees vs. opportunity cost. 2. Choosing your research topic: supply and demand considerations. What am I interested in? What am I good at? Who will supervise my doctoral research? Will I find a sponsor? Who will publish my PhD thesis? Who will read it? Who will hire me after I get my doctoral degree? How will I recover my investment? 3. How scientists work: introduction to the scientific method. Focus on causality. Induction plus deduction. Selecting hypotheses through empirical testing. Leaving ideology aside and avoiding normative statements. Seeking generality and parsimony. 4. Applying for a PhD. Structure of a research proposal. Application formalities. English language requirements. Recognition of foreign qualifications. Application fees. Selection procedure. 5. Theory building. Thinking in terms of independent, dependent and confounding variables. Identifying interesting variation. Cross-sectional and time-series variation. Strategies toward developing an original theory. 6. What is a literature review and why is it important for your research? Finding relevant literature for your research topic. An introduction to indexing and abstracting services. Web of Science, Scopus and Google Scholar. Using citation counts. 7. Reading literature on your research topic: managing your time, bibliographies, citations and references. An introduction to bibliographical management software: Endnote, Refworks and Zotero. Adding value to your literature review. 8. Data sources. Measuring variables of interest. Variable operationalisation. Proxy variables. Presenting your data: descriptive statistics. 9. Research design. The randomised experiment as an ideal. The importance of comparison: treatment and control groups. The importance of random selection. 10. Testing causality. Probability and hypothesis tests. Difference in means: the t-test. 11. Working with observational data. The importance of variation. The problem of selection bias. Looking for natural experiments. 12. Statistical methods for dealing with selection bias. Multiple linear regression. Instrumental variables. Difference in differences, fixed effect and discontinuity analyses. 13. Defending your research proposal. Knowing your selection panel. Preparing your presentation. Taking up constructive criticism and suggestions. Deflecting destructive criticism and traps. 14. Mock exam.