Mastery of the interface between the social and biological requires a multidisciplinary perspective and skills that cross domain boundaries. Soc-B is a PhD training programme designed to harness world-leading expertise in the social-biological interface across three of the UK’s top higher education institutions to produce highly employable PhD graduates with the capabilities and experience to lead and grow future research excellence in the relatively new field of biosocial science. The Soc-B Centre for Doctoral Training provides the ideal environment for working with research leaders and for creating new ones.
Soc-B is a four-year PhD programme. The first year is comprised of two biosocial training modules, two ten-week project rotations, core methodology training, and project proposal writing. Years 2-4 are focused on the PhD research topic, as well as training in advanced methods. Soc-B students also participate in three one-day workshops each year throughout the programme and placements with non-academic partners in year three.
Overall aims of the Soc-B Programme
1. An understanding of the social-biological interface
The inclusion of biomarker data in social surveys now allows for comparisons with human and animal studies that use experimental designs. When diverse types of studies converge on a model that links social experiences with biological processes, causal inferences about social context and health are strengthened. Soc-B PhD students, researchers and collaborators work together to create research and training that develops the use of both long-standing (e.g. BMI, cholesterol) along with novel (e.g. ‘omics, brain imaging) forms of bio data by equipping students with an understanding of what these bio data measure, and how they can be used by applying quantitative analysis techniques.
2. Expertise in the latest methodological developments
Soc-B PhD students will be at the forefront of methodological developments in the field of social and biomarker research, providing the research community with methodological innovation, including (but not limited to) Bayesian decision theory, econometric modelling, causal inference (e.g. Mendelian randomisation), network analysis (social network and network biology), neural reinforcement learning, sequence analysis, and technological innovations in data collection. Soc-B methodological training integrates different disciplinary methodologies.
3. Confidence in communicating research to stakeholders
Soc-B equips students with the capabilities necessary to communicate often complex research findings to audiences outside the academic sphere, thus maximising opportunities for their work to have wider societal and economic impact.