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metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
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Materials; Energy Materials and Sustainability; Materials for Structural Applications and Extreme Environments; Modeling, Theory and Computational Approaches to Materials Science and Engineering; Nanoscale
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independent, discretionary work. Responsibilities are expected to include a subset of: (1) Use advanced energy modeling to analyze energy efficiency, demand flexibility, and electrification measures in
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
). Probabilistic and reliability-based analysis applied to underground structures. Advanced subsurface characterization techniques integrating geotechnical and geophysical data. Geohazard mapping and modeling
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embryo. Cytokinesis, the division of one cell into two, is crucial for an organism's development and healthy life. Similarities in the structural and molecular organization of the division apparatus in a
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embryo. Cytokinesis, the division of one cell into two, is crucial for an organism’s development and healthy life. Similarities in the structural and molecular organization of the division apparatus in a
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, neuroscience, advanced biotechnology and medicine, environmental and occupational health, and health care policy and aging research. Our faculty are teachers, clinicians, and scientists with unparalleled
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to self-organize into complex structures. Our approach is to develop sophisticated mathematical models – informed by state-of-the-art biological knowledge and experimental data – to understand
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optimization or related inverse design techniques. While this position does not involve developing AI models, it requires close collaboration with AI researchers to ensure data is appropriately structured for AI
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using different materials, producing a comprehensive dataset of structures and their optical properties. This dataset will serve as input for AI-based design tools developed by collaborators within