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models. Minimum Qualifications Masters in Computer Science, Biomedical Engineering, or a related field. Two years of experience with machine learning, deep learning, and data analysis. Additional education
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, faculty, students, staff, and patients. Johns Hopkins University supports a flexible work model which includes four different work modalities. This role has a hybrid work arrangement with an onsite presence
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the CAPABLE intervention (up to 4 RN home visits over 4-5 months) to participants that screen into the program and agree to the services. Directly engage with participants in education, problem solving, and
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testing protocols, modeling and simulation tools, and reference materials. Analyzing experimental data to establish average and best-in-class performance benchmarks, enabling responders to assess and
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models. Optimize models for performance, scalability, and reliability. - Engage stakeholders to and identify opportunities for algorithm development and validation, control material development, and
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collaborative environment for faculty and staff. Prioritize and direct work efforts, providing guidance and direction. Conflict resolution. Champions the importance of promoting and modeling a culture of
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, staff, and patients. Johns Hopkins University supports a flexible work model which includes four different work modalities. This role has a remote work arrangement with an onsite presence of three days
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to 100 GHz, using custom and commercial test fixtures. Develop and simulate computational models of material-loaded microelectronic devices to quantify electric, acoustic, and piezoelectric fields for a
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, faculty, students, staff, and patients. Johns Hopkins University supports a flexible work model which includes four different work modalities. This role has a modified hybrid work arrangement with an onsite
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leader in the development and dissemination of community-based models of care. Assess emerging funding opportunities, weighing costs, benefits, and strategic fit. Work with outside parties and Center