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Field
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the dissolution capability of microneedle patches and transdermal drug release by plasma sample analysis focused on animal models. Finally, the research plan will include a component of simulation to describe
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
increments, which represent structural model errors (https://doi.org/10.1029/2023MS003757). When applied online to global ice-ocean simulations, this neural network substantially improves sea ice simulation
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and optimization of measurement-based quantum computing protocols for quantum simulation of quantum many-body models. Preference will be given to candidates familiar with the stabilizer formalism and
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real-time simulation platforms. Knowledge with designing, modeling, or hardware prototyping of power electronic converters. Proficiency in Python and/or C. Ability to work both independently and
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, or a closely related field. Preferred Qualification: Research experience in biomedical implants, animal models, and aging/Alzheimer’s disease. Research experience in biomaterials, neuroscience
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theories. Develops advanced analytical models and systems and provides solutions and analyses to support strategic and tactical decisions. Adheres to University and unit-level policies and procedures and
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. Key responsibilities include: Simulating regional air quality using numerical models (e.g., WRF-Chem, CMAQ) Improving wildfire emission estimates and smoke plume rise representation Evaluating model
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, the cell biology of photoreceptors and hair cells, and potential treatments. We utilize mouse models and various approaches in molecular and cellular biology, biochemistry, omics, bioinformatics
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molecular dynamics simulations. This position emphasizes research in the modeling of complex chemical systems, where the candidate will integrate advanced simulation techniques with modern machine learning
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working in radiological environment. Experience in heat transfer and thermal modeling/simulation using finite-element analysis (FEA) or other software. Ability to work within a multi-disciplinary team