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Field
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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, through developing predictive models and new experimental methods and instrumentation, to design creative and cost effective CO2 trapping processes. The need is urgent, the task is challenging and a
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. Applying Operations Research techniques to support the selection among predefined extraction methods. Developing and using Machine Learning models for quality prediction and control of phosphate ore
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assessment models and evaluate the nutritional quality of foods. Build risk-benefit assessment models to quantify and predict the health impacts of new food products. A central case study will explore
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thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction and optimization. Collaborating with experimentalists and industry
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contribute. Since early risk prediction and timely intervention can mitigate vision loss, it is critical that we fully understand the underlying cause(s). This project aims to identify biomarkers in the eye
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, model predictive control, parallel computing using JAX and rapid online learning, is highly desirable, but candidates demonstrating an ability and willingness to become familiar with these topics and able
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/or high-temperature heat pumps based on power cycles. Design thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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from antigen presentation, prediction of immunogenic neoantigens, to T cell-mediated control of cutaneous squamous cell carcinoma and melanoma, utilizing immunological, cellular and molecular biological