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. The student will support research activities including implementing and testing algorithms, conducting experiments, reviewing technical literature, analyzing results, and assisting with research publications
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methods for additive manufacturing applications, including ANNs and evolutionary genetic algorithms for process optimization supported by programming knowledge (e.g. Matlab, Python). Hands-on experience
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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techniques, including genetic algorithms, to optimize transducer architectures. 3, Develop computational mechanics workflows to predict material properties and guide the design of acoustic metamaterials
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demonstrated ability to conduct innovative, independent research and contribute to collaborative projects. Areas of expertise should include sonogenetics, cellular and molecular engineering, genetically encoded
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help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
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in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems tailored to dynamic, human-centered environments. They may
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predictive analytics Human factors, behavior science, and patient-centered design Advanced computing and scalable algorithms Decision science and learning health systems design Qualifications Required: Ph.D