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for publications in journals and conferences collaborate with industry partners and leaders in the field of FPGA-based machine learning accelerators About you The University values courage and creativity; openness
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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for preprocessing, integration, and modeling of heterogeneous data (spatial, temporal, tabular) -Conduct research in explainable AI and uncertainty quantification applied to agronomic decisions. -Collaborate with
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-scale Modeling, Evolutionary Computation, Diffusion models, Reinforcement Learning. The successful candidate will work in a highly collaborative and international environment. Contact Information
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students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading
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are desirable. We particularly encourage applicants with expertise in Multi-scale Modeling, Evolutionary Computation, Diffusion models, Reinforcement Learning. The successful candidate will work in a highly
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: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics
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opportunity to contribute to cutting-edge research at the intersection of artificial intelligence, machine learning, and healthcare. The successful candidate will develop and apply advanced machine learning
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studies and tissue sample collections and analysis Perform all phases of experimental investigations in consultation with the faculty advisor(s) Collaborate with other researchers in the collaborative
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Claire O’Callaghan, the successful candidate will join a collaborative, interdisciplinary team, where they will be supported to develop their own research questions and lead projects. Experience in