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outcomes ●casual representation learning for real-world data ● deep learning interpretation, fairness and robustness ●Regularly conduct computational experiments to execute algorithms on various health and
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pathology by developing, applying, and optimizing pipelines for the analysis of scanned anatomic pathology slides. This work is conducted within Dr. Nathan Pankratz’s laboratory in the Division
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faculty in developing theory and application tools for artificial intelligence (AI), and training efficient data analytics. 60% - Leading research in AI will include generative models, algorithms and
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(PI and Co-I) and the cytokine reference laboratory in developing assays, scheduling the assays and receipt of data. 10% effort: Writing grants, study protocols, reports, publications and presenting
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implementation of various projects, including (but not limited to) scaling, algorithm development, scaled score development and documentation. Support the creation, management, and retention of large-scale data
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Khani. Job Duties: Developing new models, optimization algorithms, and machine learning algorithms for transportation systems and services (40%). Applying the models and algorithms to new transportation
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intern in multiagent trajectory optimization. The successful candidate will help develop and implement mixed-integer and nonlinear programming methods for coordinating multiagent UAV systems. This role
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candidate to fill one Research Professional 5 - Educational Research position. The position will primarily focus on building large datasets and developing algorithms to detect cognitive/affective states
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hierarchies during cardiac, endothelial and hematopoietic development. Responsibility: * Develop or integrate novel statistical methods and algorithms for analyzing large-scale -omics data, including gene