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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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Job Reference: 1168098 About the Role: You will play a key role in advancing distributed and adaptive AI methods, focusing on scalable software frameworks, learning algorithms, and orchestration
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Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. Your key responsibilities will be to: design and implement mathematical algorithms, and facilitate their integration into Magma engage with
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, Massachusetts. Your key responsibilities will be to: design and implement mathematical algorithms, and facilitate their integration into Magma engage with users, researchers, and developers, both internally
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learning and mechanistic modelling, sensor network development, efficient data sorting and processing algorithms, real-time and model predictive control, and transformative applications in the wastewater
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algorithms for computing MML solutions beyond the one-dimensional case. Extend existing dynamic programming approaches to higher-dimensional problems or develop novel approximation methods that preserve
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planning algorithms for GPS-denied lunar environments and extreme operational conditions stochastic optimisation frameworks for mission-critical decision-making under uncertainty Research areas and technical
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compelling content and messaging for social media, website, and e-communications in alignment with Institute branding and audience needs. Monitor analytics, platform algorithms, and audience behaviour
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theory, ergodic theory, differential geometry, data science, and/or machine learning. Implement algorithms that efficiently analyse dynamical systems arising from idealised models or data. Collaborative
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. The organisation is currently working on research project(s) related to the release of a new digital product that conducts optimisation of AI algorithms for sustainable home retrofitting solutions. Opportunity