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-parameter flow-cytometry, as well as murine models and human organoid technology to investigate mechanisms of longevity of immunological T and B cell memory. A strong interest in quantitative disciplines
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systems, and space applications. We combine theory, physics-based simulations, machine learning, and autonomous workflows to understand and design materials that can perform under conditions where
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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. Integrate physical laws, experimental data, and simulation results into unified machine learning frameworks to improve model robustness and generalizability. Conduct data preprocessing, model training, and
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classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and feedback Develop active learning and
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, Computational Linguistics, Machine learning, Computer Engineering or related fields Preferred Qualifications: ● Strong experience implementing and training deep learning models in PyTorch, with attention
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DEVCOM Analysis Center. Topics of particular interest include: 1. Development of novel machine learning and AI models, as well as the adaptation of existing approaches for AI-enabled decision aid systems
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/Planning Internal Number: 6832149 Part Time Lecturer - Architecture About the Opportunity The Lecturer will teach introductory courses in architectural drawing, sketching, studio design, computer modeling
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virtual reality development, machine learning, or advanced data analyses and modeling are highly desirable. Position Status Full Time Posting Number 25FA0682 Posting Open Date Posting Close Date
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Department: Computer Languages and Systems Research profile: Model-driven engineering and intelligent and inclusive systems in health and education Position number: DF03222 Area of knowledge: Computer