We are seeking the opportunity to recruit an inaugural cohort of up to 5 PhD students to work on interdisciplinary computational social science projects under the supervision of CSS Lab faculty. The core faculty/supervisor team includes:
- Dr. Olga Boichak (School of Art, Communication and English, Faculty of Arts and Social Sciences)
- Professor Monika Bednarek (School of Humanities, Faculty of Arts and Social Sciences)
- Professor Eduardo G. Altmann (School of Mathematics and Statistics, Faculty of Science)
- Professor Kalervo Gulson (School of Education and Social Work, Faculty of Arts and Social Sciences)
- Associate Professor Tristram Alexander (School of Physics, Faculty of Science)
- Dr. Aim Sinpeng (School of Social and Political Sciences, Faculty of Arts and Social Sciences)
- Dr. Joanne Gray (School of Art, Communication and English, Faculty of Arts and Social Sciences)
All projects will build on the existing strengths and expertise of the Social Media and Data Science research group and affiliated faculty around the modeling and analysis of data-driven representations of individuals and communities. and the algorithmic biases associated with these emerging regimes of knowledge production. Core faculty bring a significant track record of research excellence in three distinct areas of computational social science: language and topic modeling (Bednarek, Boichak), network analysis and community sensing (Altmann, Alexander), machine learning and artificial intelligence (Sinpeng, Gray, Gulson). From different disciplines in two faculties, they have each demonstrated deep graduate research leadership in relation to opportunities, as well as bringing successful innovations to the HDR research training space.
We invite applicants with a background in computational social sciences, digital humanities and/or data science with strong regional and/or domain expertise. The successful candidate will join an interdisciplinary research team in the lab, which is located in the research-intensive interdisciplinary environment of the Sydney Social Sciences and Humanities Advanced Research Center (SSSHARC) at the University of Sydney. The supervision team will generally consist of a supervisor and an associate supervisor from different disciplinary backgrounds. This will expose doctoral students to different traditions within the computational social sciences, allow challenging research questions to be tackled, and contribute to the creation of long-term multidisciplinary collaborations within the University.
Successful projects will use a range of approaches for a critical understanding of big data and computation in their sociotechnical contexts. We are particularly looking for projects that would involve creating, applying, testing or evaluating a range of computational approaches (e.g. data visualization, corpus linguistics, topic modeling, network analysis, machine learning Statistical Automation) to investigate various potential datasets (including those collected from social media, news media, policy documents, etc.) and answer important theoretical and empirical questions to address important social issues in the contemporary society.
The theoretical social science frameworks that underpin the project can come from a range of social science and humanities disciplines. Of particular interest are projects that explore the development of algorithmic systems and policies and critically investigate their social, cultural and ethical implications. Projects can cover a wide range of social areas, including but not limited to human rights, public discourse, digital literacy, safety and security, educational outcomes, social studies of science, etc Computer methods can be combined, improved, questioned or enriched with traditional methods by triangulating approaches.