This is a research degree requiring an original and significant contribution to knowledge in the field of learning analytics. It is the traditional path for those wishing to pursue a career in research or academic life. The PhD provides an opportunity for graduates to acquire high-level research skills and substantially deepen their knowledge in this area. This course has been developed as a response to a global talent gap for people with data science knowledge, as identified and reported by the McKinsey Global Institute study (2011). The study predicted a shortfall by 2018 of nearly 200,000 data scientists and 1.5 million managers with the capability to make decisions using big data in the United States alone. The dramatic growth of data in every conceivable industry, from oceanography to market research, presents another major driving force in generating unprecedented global demand for data science skills. Course structure The Doctor of Philosophy is structured in three phases. Phase 1: Students negotiate a doctoral study plan with their supervisor. This plan makes explicit the kinds of support each student requires. A formal doctoral assessment is undertaken at the end of Phase 1 in which the candidates present a full proposal for assessment, which is a prerequisite for entering Phase 2. Phase 2: Students develop their individual program of research, and their readiness to enter Phase 3 is assessed at the end of Phase 2. Phase 3: Candidates engage in the preparation and submission of a major thesis, which makes a sustained contribution to knowledge in their field of inquiry. Careers This degree prepares data scientists for leadership positions in teaching, management and research. There are opportunities for developing a career on a national and international level.