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Field
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include: Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines. Build reproducible research pipelines and maintain reliable
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propulsion, onboard microgrids, EMS algorithms, and real-time validation platforms. Project & Research Responsibilities: Participate in and support the execution of the research project with the Principal
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to the design, modelling, simulation, validation, and optimization of electric vessel power systems, with strong emphasis on battery-based propulsion, onboard microgrids, EMS algorithms, and real-time validation
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the neural mechanisms underlying goal switching and behavioural strategy selection, linking algorithmic theories of behaviour to defined microcircuits and pathways. The position will employ a multidisciplinary
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progress. Ability and willingness to work some flexible hours. Extensive experience in large-scale pre-training of large language model. Experienced in developing machine learning algorithms and large
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quantum spectroscopy, sensing, photonics, semiconductor quantum optics, quantum materials, and quantum algorithms. Postdoctoral Fellows will collaborate with at least one QRI Fellow Mentor. Eligibility
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representations for decision-making and control of aerial robots, ground vehicles, quadrupeds, and humanoids. We are particularly interested in candidates who can bridge algorithmic innovation with real-system
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under project guidance. Documentation: Produce and maintain technical documentation, including pipeline workflows, algorithms, QC procedures, and SOPs to ensure reproducibility. Communication: Communicate
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of marine geophysical survey and machine learning algorithms; Job Requirements: A Bachelor degree in geophysics or equivalent and A PhD degree in geophysics / geomechanics or equivalent from a recognized
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learning and deep learning algorithms for computational biology and biomedical applications. • Support the execution of funded research projects by meeting technical milestones, maintaining research