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ADC performance against acute myeloid leukaemia (AML). Laboratory experiments and machine learning models will be implemented to achieve the following aims: Develop a random forest regression model
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experience in manufacturing systems modeling, simulation (i.e., DES), and digital twins. • Good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production
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and generous family tuition benefits. The teaching load for this position is five course sections per academic year. The Freeman College embraces the teacher-scholar model. Our new colleague will show
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at the interface of biological physics, agent-based simulations and machine learning to turn quantitative imaging data into a mechanistic, testable model of spindle positioning. In particular, we expect
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of cybersecurity. Examples areas of interest include, but aren’t limited to: ● Problems at the intersection of cybersecurity and artificial intelligence/machine learning (AI/ML) ● Systems and
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fluorescence microscopy (SMLM, SIM), integrating physical-mathematical models, machine learning, and compressed sensing for accurate and efficient reconstructions. Applicants must submit a project implementing
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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during
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systems, devices (including fabrication) and sensors, robotics and automation, artificial intelligence and machine learning, advanced electronics, and communications. Our faculty are particularly encouraged
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years and in the relevant areas of Machine Learning / Artificial Intelligence, Credit Risk Modeling and Operations Optimization Modeling; The candidate must have strong programming skills in Python, and
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allow users to input CDR forcing (e.g., alkalinity addition) and produce day-by-day forecasts of CO2 uptake and storage durability. The project combines physics-based modeling, machine learning, and high