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Field
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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models/tools. Experience with large, varied datasets. Experience working with soil, water, and plant sensors and remote sensing technology. Other Requirements: This position requires physical activities
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-guided) Evolutionary trajectory analysis and fitness landscape modeling Integration of predictive algorithms with experimental iteration cycles High-throughput screening and selection platform development
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interaction Research and design multi-modal foundation models to enhance robot autonomy, social perception and collaborative decision making Design and build machine learning algorithms and frameworks
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials
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-edge sensors with current computational tools and machine/deep learning. As a Postdoctoral Researcher, you will be a key member of our team responsible for designing the seamless integration
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scalability and resource efficiency through the development of cooperative, distributed AI algorithms, optimising data, energy, and processing resources while adapting to the different computational
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project integrates expertise across multiple levels—from circuits and architectures to algorithms, models, and systems—and includes opportunities for radiation testing at the NASA Space Radiation Laboratory
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of this instrument ongoing, we make critical contributions to silicon sensor quality control, the initial steps of module assembly, thermal quality control of local supports. The group is led by Dr Seth Zenz, and