260 data-"https:" "https:" "https:" "https:" "https:" "https:" "Here We Are" uni jobs at Monash University in Australia
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nutritional data into a user-friendly platform, enabling consumers, restaurants, and policymakers to make informed food choices and reduce diet-related emissions. Required knowledge Data analytics and software
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on clinical, genomics and functional dependency data (CRISPR, drug screens). Brain tumours represent the second most common cancer and the most common solid tumour in childhood in general. Paediatric brain
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Candidates should hold a previous degree (Bachelor’s and/or Master’s) in Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering, with demonstrated knowledge in machine
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While deep learning has shown remarkable performance in medical imaging benchmarks, translating these results to real-world clinical deployment remains challenging. Models trained on data from one
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existing tokenization frameworks, analyzing potential risks, and developing novel security protocols to protect sensitive data and ensure the integrity of tokenized assets. Applicants will investigate
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environments—such as MOOCs, online degrees, and data-intensive Learning Management Systems—necessitate scalable solutions to provide timely, high-quality feedback. However, existing AI-powered assessment systems
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Multi-View Learning in CV and NLP Robust Active Learning Under Distribution Drift Data-Efficient Deep Learning for De Novo Molecular Design from Analytical Spectra Hybrid Quantum–Classical Algorithms
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) to support surgeons, operating room technicians, and other professionals in and around operating room activities. Particular areas that may be explored are: Immersive OR analytics: using XR to analyse data
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Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum
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Minimum Message Length (MML) is an elegant information-theoretic framework for statistical inference and model selection developed by Chris Wallace and colleagues. The fundamental insight of MML is