Training and development
Queen Mary University of London (QMUL) has a strong reputation for innovation through inter-disciplinary and cross-faculty collaboration. The Research Excellence Framework 2014 rated QMUL 5th in the UK for "world-leading or internationally excellent" research outputs, and HEFCE 2013 noted that QMUL has the highest rate for timely PhD completion of any UK university.
Pending assessment the student may need training in the following:
At the CPCPH we run a masters course in Global health and Innovation, which includes a research methods and advanced research methods modules. The student could either attend one or both modules to re-familiarise themselves with research approaches and gain new knowledge. This will prepare the student for mixed-methods approaches and for qualitative data analysis including thematic analysis.
Statistical training will be given on the Research methods course but where necessary we will provide specialist training with one or two of our own statisticians from the centre for health sciences. Additionally the Royal Statistical Society run a variety of training courses throughout the year that may be of use.
Systematic narrative and critical literature reviewing
Within CPCPH we have considerable expertise in different aspects of conducting reviews of methodology, including search strategies, data extraction, issues with identifying methodology from papers, and presenting results. The student will receive appropriate training from CPCPH staff and if staff are unavailable we will organise attendence on one of the many courses available in this field.
Machine learning and computational training
The Faculty of Science and Engineering provides expertise and teaching in machine learning and related fields, and The Blizard Institute, where the CPCPH is based, has relationships with this faculty through the programmes including Queen Mary Innovation and the "CANBUILD - deconstructing cancer" project. The student will be able to access modules relating to the computational element of this PhD, contributing to the existing reputation the Blizard Institute has for interdisciplinary research.
The university run excellent courses for the software applications they will need to be proficient in, for example Endnote, Microsoft Word and PowerPoint. We can also include the PhD student in our M.Sc. for Global Health and Innovation modules such as: introductions to the library and searching electronic data bases. Additionally, there are excellent short course in using statistical software packages. Other courses that we would expect the student to attend are Problem Based Learning (PBL) training to contribute to not only their own training but that of others. This will also help foster a working team spirit within the CPCPH.