Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
The Oxford Internet Institute has an exciting opportunity to join the Governance of Emerging Technologies research programme, working under the supervision of Professor Brent Mittelstadt and
-
EPSRC-funded project, MAPFSI that will be focused on developing experimentally-validated computational algorithms for fluid-structure interaction problems including multiphysics effect of electromagnetism
-
processes, Bayesian inference, signal models, sampling theory, sensing techniques, optimisation theory and algorithms, multi-modal data processing, high-performance computing, mathematical image analysis
-
, sensing techniques, optimisation theory and algorithms, multi-modal data processing, high-performance computing, mathematical image analysis, geometric modelling, acoustic signal propagation, Monte Carlo
-
aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
-
, including: Robot Learning: Creating algorithms that empower robots to learn autonomously from interactions and adjust to new tasks. Manipulation: Enhancing techniques for precise and adaptable object handling
-
Full-time: 35 hours per week Fixed-term: 31st March 2026 The School of Informatics at the University of Edinburgh invites applications for 2 Post-doctoral Researcher positions in Quantum Machine
-
algorithms. The research focuses on wind energy applications, creating a compelling sustainability narrative: developing more efficient computational methods to optimize wind farm performance, which in turn
-
research initiative funded by ARIA, titled Aggregating Safety Preferences for AI Systems: A Social Choice Approach. The project operates at the interface of AI safety and computational social choice, and
-
explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design