Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
may also be considered. Candidates should be aware of and meet the entry requirements for the university hosting the PhD studentship. Funding Notes The programme is four years and starts in September
-
previous experience of using CFD would be useful but not essential. Funding Notes The programme is four years and starts in September 2026. Funding includes full UK fees, tax-free stipend (2025/2026 stipend
-
innovative use of technology and computation within arts, humanities and heritage research as both a method of inquiry and a means of dissemination. Digital culture is everywhere, and it is driven by cultural
-
the research life of the University. PGR students undertake their own programme of research, supervised by an academic team, and also contribute to the wider research culture, output and impact of
-
Details This project explores the textual transmission and cultural influence of Petrarch’s poetry across different literary traditions and languages, integrating computational methods to enhance
-
workflows, but also by helping to reimagine digital editions beyond the constraints of print-based models. In particular, it researches and analyses how computational and AI-driven methods, including but not
-
. This paves the way for the application of MPC to large-scale systems, since the computational bottleneck is removed. The basic challenge is how to coordinate the distributed decision making of agents so that
-
collaborative researcher to lead the design and implementation of both experimental and computational modelling studies. In this role, you will develop innovative diagnostics to measure how various media
-
engineering, signal processing, electrical engineering or a related subject. Full details of how to apply can be found at the following link: https://www.sheffield.ac.uk/acse/research-degrees/applyphd
-
skill via an intrinsic reward. Science Advances, 10(13), eadj3824. https://www.science.org/doi/full/10.1126/sciadv.adj3824 Durstewitz, D., Koppe*, G., & Toutounji*, H. (2016). Computational models as