Lecturer.2.01 - AI Research Scientist Gauteng

A candidate must hold a PhD in Computer Science, specialising in Artificial Intelligence, Machine Learning, or a closely related field (at the time of appointment). Demonstrated ability to apply AI methods to non-computational, domain-driven research questions (evidence of work in the humanities, social sciences, or interpretive social science is highly desirable).

Experience (Research and Professional):

Proven competency in AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and programming languages (Python required; R an advantage).

Natural Language Processing (e.g., large language models, topic modelling, text classification, named entity recognition, retrieval-augmented generation); Computer vision or multimodal analysis (e.g., for visual archives, media, or material culture); Scalable data acquisition and processing (e.g., web scraping, API integration, data cleaning, dataset curation for specific research contexts); Integration of AI into research pipelines (e.g., automating coding, qualitative-quantitative integration, pattern detection in historical or literary corpora). Strong understanding of the challenges and opportunities of applying AI in African contexts and/or the Global South, including issues of data scarcity, algorithmic bias, epistemic diversity, and ethical AI design. Track record of collaborative, cross-disciplinary research (e.g., as a co-investigator, data scientist embedded in a non-CS project, or consultant on complex research infrastructure).

Work proactively across the Faculty of Humanities and the MIND Institute to identify, scope, and co-design AI-driven enhancements to ongoing research projects in areas such as literary studies, historical archives, media analysis, social science research, education data, and arts-based research. Lead the technical implementation of AI methods for data acquisition for the Faculty of Humanities (e.g., building scalable pipelines for digitisation or web-based corpora) and data analysis (e.g., deploying LLMs for historical text analysis, computer vision for visual archives, or predictive models for social science datasets) and build and support MIND (e.g. automated workflow processes to support research and administrative functions) Provide training, capacity building, and ongoing consultation to humanities researchers and their postgraduate students, enabling them to critically and effectively use AI tools in their work. Contribute to the research output of the Chair and partner units by co-authoring publications, with an average of at least two peer-reviewed articles per year (international, ISI-indexed where appropriate). Mentor and co-supervise PhD and Master’s students on AI-integrated humanities projects. Contribute to the research ethos and vision of the Chair through participation in seminars, research leadership, dialogue, and ideation. Contribute to the operation and sustainability of the Chair’s laboratory and facilities, including software and hardware infrastructure for AI research. Support fundraising efforts through grant applications and partnership development. Developing a personal research profile alongside the Chair’s through presentations, public engagement, social media, and online presence.

Professional and research independence, with mentorship and guidance from senior researchers while operating at a lecturer-equivalent level of responsibility. Opportunity to shape the strategic integration of AI across a large, diverse Faculty of Humanities. Experience in research leadership, cross-disciplinary collaboration, and advanced research infrastructure development. Engagement in cutting-edge AI research grounded in real-world humanities questions, contributing to African-led Digital Humanities.

Closing date: 01 September 2026