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The Adelaide Graduate Research School (AGRS) and Australian Energy Market Operator are partnering to create 3 remote internship opportunities for University of Adelaide PhD students, to contribute
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predictive model and conduct a sensitivity study to investigate the multiple factors on the performance of the flow meter. Funding The student will be in receipt of a stipend payment; the Research Council
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Department: Fisher College | Operations and Business Analytics The candidate will be expected to work closely with the PI to play a leading role on a team that has two broad objectives: 1) creating drug-level
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neuroscience-based approach to understanding decision-making, learning and mental representations in humans and how these processes go awry in neurological and psychiatric disorders. In close collaboration with
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learning (ML) for high-fidelity data ‘stitching’. The integration of data from multiple analytical platforms is critical for advancing the understanding of complex biological and chemical systems. This work
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impurities and scrap-blends on the corrosion performance of alloys evaluated through different corrosion tests supported by advanced characterisation techniques. The objectives are as follows: To evaluate
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nanobelts. Your profile: We are looking for experimentally skilled candidates, ideally experienced in multiple-step organic synthesis Prior work on fused aromatic compounds is certainly advantageous
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4 year PhD Studentship: Deciphering how domain organisation regulates heparan sulphate function University of Nottingham, School of Medicine Supervisors: Prof Cathy Merry, Prof. Kenton Arkill, Dr
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multiple objectives in real-time. The complexity of coordinating these distributed systems while ensuring stability and optimal performance presents a significant technical barrier that must be overcome
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diffusion models usually needs to access a pre-trained model multiple times sequentially to generate high-quality images or videos, which is time-consuming. The training process of diffusion models is also