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Field
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systems, urban technology, networks science, information, decision and complex networks, computational and infrastructure intelligence, revenue and finance, complex systems architectural design framework
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imagery Engineer advanced architectural components and workflows for efficient and effective foundation model training and fine-tuning Devise data curation and balancing schemes Rigorously assess model
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 2 months ago
experimentalists, cancer research scientists and biomedical engineers. Qualifications The candidate must hold a PhD in one of these disciplines: Mathematics, Numerical Analysis, Computational Mathematics
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on reliability, security, and resilience of microgrid systems. This includes advanced control system design, modeling and analysis, control architecture design and communication-based control and optimization
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underlying human disease. The team brings together diverse expertise, ranging from work with mutant stem cell-derived beta cell organoids, engineered mouse models, single cell epigenomics, large-scale genetic
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scientific facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN researches and
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computer engineering, computer science, physics, chemistry, materials science, chemical engineering, or a related field. Demonstrated ability to communicate research results in peer-reviewed publications and
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Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers
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: Doctoral degree in a related field, such as Architecture, Civil Engineering, Robotics, etc. Excellent track record of research and publications related to the job description Strong scientific writing and
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Optimization:Design, build, and fine-tune LLMs and other AI models to address complex challenges in multimodal learning.Develop scalable and efficient architectures for deploying models in real-world environments. 3