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the engineering and fundamental research underlying a multi-chamber cancer-detection device from concept through integrated laboratory. The role emphasizes device innovation, robust design, and manufacturable
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vehicle validation. Design and implement machine learning models that capture the complexity and variability of real-world traffic situations, including unusual pedestrian behaviors, edge cases, and multi
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maintaining IACUC protocols, (4) experience with various coagulation assays, and (5) biomedical engineering student management experience Core Responsibilities: Responsible for performing independent research
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to benchmark its performance. This position offers a unique opportunity to work on a multi-disciplinary project with a team of scientists and engineers and experts in commercialization and translational research
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fundamental research and applied validation underlying a multi-chamber cancer-detection device from concept through integrated laboratory demonstration. You will develop user-oriented sample-handling and assay
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and formal training in engineering is preferred. Core Responsibilities: Responsible for performing independent research Responsible for maintaining laboratory equipment used to perform research
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Expert in advanced machine learning such as multi-agent generative AI, LLMs, Diffusion models, and traditional machine learning techniques Expert in CALPHAD-based ICME techniques Expert in combining