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biology. Strong background in protein and antibody engineering, including purification and affinity maturation. Proficiency in molecular biology techniques, tissue culture, and disease modeling. Ability
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highly integrated, multidisciplinary approach involving enzyme kinetics, molecular modeling, and biological testing to discover, design, and develop new therapeutics. This position is also anticipated
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technologies including thermal energy storage (TES) and hydrogen technologies integrating with concentrating solar power (CSP). Responsibilities under this position include leading research work on modeling
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, metabolomics, clinical samples, and animal models to accomplish these goals. The results will lead to the development of novel therapeutic strategies for the clinically relevant molecular subsets of lung cancer
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a postdoctoral scholar to lead collaborative efforts among researchers at the University of Utah and UC San Diego in developing and applying methods in predictive and causal modeling of complex
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems
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postdoctoral fellow interested in gaining training and experience in disease modelling and transnational science. The successful candidate will lead collaborative efforts among basic and clinical researchers and
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Computing (e.g., memristor modeling/simulation/manufacturing) and Edge AI related areas (e.g., AI algorithms, AI accelerator, VLSI). Background Investigation Statement: Prior to hiring, the final candidate(s
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. Recruits and screens participants, reviews records and surveys, and maintains databases. Performs routine data analysis and prepares reports, data visualizations, and models. Essential Functions
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for clinical use. Generative and Predictive AI for Clinical Decision Support and Statistical Inference Develop biologically informed statistical methods and uncertainty estimation models to train deep learning