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developers based in Australia and the USA to optimize therapeutic strategies for mRNA-based therapies. About Monash University At Monash , work feels different. There’s a sense of belonging, from contributing
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Mixed-Integer Programming (MIP) solvers are very powerful tools to solve combinatorial problems that arise in many industries. Modern MIP solvers usually run a sequence of algorithms to solve
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to contribute to novel encapsulation methods, optimize formulations, and characterize systems using advanced analytical techniques. You will collaborate with interdisciplinary teams to explore applications in
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) in the context of neural-symbolic systems Discrete optimization and/or Boolean satisfiability Exact and approximate model counting About Monash University At Monash , work feels different. There’s a
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determining the appropriate design pattern for a specific scenario, identifying relevant quality attributes for a particular design choice, and recognizing the optimal timing for implementing a refactoring
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at primary care and offer optimal use of scarce health system resources. The model will be trained using skin images (clinical and/or dermoscopic) to identify disease relevant features and accurately diagnosis
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, Weighted Partial MaxSAT, pseudo-Boolean optimisation etc.) over a fixed horizon, and solved optimally using off-the-shelf solvers. One important limitation of this learning and planning framework is the
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issues in Mobile Apps) that have the largest impact on end-users and humanity. Finally, this project will leverage a multi-objective optimisation approach to find a set of optimal QA prioritisation
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intelligence techniques (e.g., Deep Learning, Statistics, ML, Optimization) in order to (1) understand the nature of critical software defects like vulnerabilities; (2) predict; (3) highlight vulnerable code; (4
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on social dilemmas, i.e., situations where poor group outcomes arise from optimal individual choices. We use this framework to study: Multi-agent Systems and AI, Social Systems, and Models in Biology and