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of Materials, analytical and numerical Data-Driven Engineering Design and Optimization Algorithms Surrogate Modeling (e.g., Kriging, Gaussian Processes, Neural Networks, etc.) Scientific Programming (e.g
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Aalborg University’s problem-based learning (PBL) model. The position is anchored in the HumanMachineInteraction research environment at Department of Architecture, Design and Media Technology at Aalborg
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is a DDLS PhD student in Data driven cell and molecular biology. Data driven cell and molecular biology covers research that fundamentally transforms our knowledge about how cells function by peering
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, spanning data preparation, acquisition, ingestion, integration, model development, training, and evaluation across multiple modalities. This position engages collaboratively with faculty, PhD students, and
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In this project, the selected candidate will join us in conducting research in statistical learning, developing data-driven methods to learn models of large-scale signals and systems from data
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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | 29 days ago
to investigate Wnt signaling in different model systems, including Drosophila, Hydra and cultured cells. Technology development will be in the areas of precise and efficient gene tagging, pooled in vitro and in
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biological mechanisms is necessary to establish mechanistic models for tree distribution and growth that will improve our predictions of tree species' range-shifts as well as productivity changes within
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mangament in numerical models, including advanced calibration strategies from data (observations, measurements, other model predictions) and uncertainty reduction. Scientific context Many engineering and
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cartilage tissue engineering? Are you driven to develop novel in silico frameworks that deepen mechanistic understanding of tissue growth and inform in vitro experiments? Then you might be our next PhD
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-methods… Requirements Specific Requirements You are an enthusiastic researcher driven by curiosity and: Have an affinity with statistical or mathematical modeling, and (some) programming experience