Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Seizure prediction algorithms will be developed using the one-of-a-kind ultra-long-term human intracranial EEG dataset obtained from the Neurovista Corporation clinical trial of their Seizure
-
I work on the study of massive and supermassive stars (10-100,000 solar masses); the first generations of stars in the universe (Pop III stars); evolution of rotating massive stars and the spin
-
these challenges, calling for the development of responsible AI systems that are transparent, trustworthy, and aligned with human values in educational contexts. This PhD project aims to design, develop, and
-
period to a 'developing' country. Total scholarship value $6000 Number offered Two See details Bachelor of Education (Honours) in Secondary Education and Bachelor of Arts Rebecca Having a scholarship has
-
initiatives. As the successful candidate, you will be responsible for: Leading the development and delivery of strategic HR Business Partnering services aligned to University and portfolio priorities. Coaching
-
the Universe, e.g., where did the carbon in your bodies come from? What type of star made it? Generally we study stars in their final phases of evolution, when they become ageing red giants which is when
-
-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
-
, yielding negligible performance gains or even inducing catastrophic forgetting. To bridge the gap between theoretical AL and real-world deployment, this PhD project will develop resilient active learning
-
the power of LLMs to develop advanced computational methods for the detection and mitigation of misinformation and disinformation. More specific objectives are: To investigate the effectiveness of large
-
these issues is critical for building trustworthy multimodal AI systems. Research Objectives The goal of this PhD project is to develop scalable Bayesian uncertainty estimation frameworks for single- and multi