Topic: uncertainty quantification

Develop methods combining bifurcation analysis, robust optimisation and uncertainty quantification for nonlinear structural dynamics and aeroelastic flutter mitigation in high-altitude, long-endurance drones. The work includes modelling uncertain nonlinear systems, numerical implementation and comparative evaluation of robust bifurcation-diagram optimisation. The ANR FlexHALE appointment lasts 18 months in Inria Saclay’s PLATON team, with a start no later than January 2027 and approximate gross pay of €2,700 per month.

UKRI and EPSRC are funding speculative, high-risk fundamental research with the potential to produce a step change in the explainability of future AI systems. The call welcomes work on mechanistic interpretability, output reasoning, process examination, imposed explainability, uncertainty quantification, and novel approaches beyond those examples.

Neural decoding is essential for understanding the association between neural activity and behavior. A prerequisite for most decoding methods is spike sorting, the assignment of action potentials (or spikes) to individual neurons. Current spike sorting algorithms, however, can be inaccurate and do not properly model uncertainty of spike assignments, therefore discarding information that could potentially improve decoding performance. Recent advances in high-channel-count probes like Neuropixels (NP) and extracellular analysis pipelines allow for extracting a rich set of spike features to direc