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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 24-Jun-25 Location: Minneapolis, Minnesota Categories: Academic/Faculty Mathematics/Statistics Additional Information
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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experimental results. Ability to work in interdisciplinary teams that involve experimentalists and modelers. Criteria of candidates: PhD in Chemical/Mechanical Engineering, Energy, Applied Chemistry, Applied
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resilience and its change over time in the past (based on Earth observation data), present and future (based on Earth system model simulations for different future scenarios, e.g. using the CMIP6 ensemble and
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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pathways driving leukemic transformation during haematopoietic development. The successful candidate will use in vitro differentiation systems (ESC/iPSC) to model normal and malignant haematopoiesis
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Johansson. Professor Johansson works at the interface of research and operational public health using statistical and mathematical models to improve surveillance, prevention, and control of infectious
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molecular biological and quantitative techniques including microscopy, flow cytometry, computational/mathematical modeling, and utilizes approaches from synthetic biology and complex biological systems