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to minimize algorithmic bias. Develop expertise in evaluating AI devices that can adapt and learn post-deployment, including understanding evolving algorithms and creating methodologies to assess algorithm
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development of transparent, closed-loop control system for individualized diuretic closing including the validation and advancement of machine-learning and control algorithms, building production-oriented
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is interested in understanding the neural and algorithmic basis of sensory-guided behaviors in terrestrial animals. We have developed behavioral tasks in mice using stimuli and situations
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diseases and their impact on interstate and international trade and community health. They will learn surveillance procedures, diagnostic testing methodologies and algorithms, serological diagnostic methods
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for characterization of CT images. Machine and Deep learning: Develop and implement machine learning and deep learning algorithms to built detection and prediction models for CT images Performance Evaluation: Conduct
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: Experience with developing efficient numerical algorithms and modifying electronic structure DFT or quantum chemistry software (e.g. Quantum Espresso, PySCF, GPAW), fluency with electronic structure theory and
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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postdoctoral fellows to perform cutting-edge research in AI for radiation therapy. Research areas include developing and implementing AI techniques for image-guided radiation therapy, such as image
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hospitals. PRIMARY DUTIES AND RESPONSIBILITIES: The qualified candidate will focus on developing new algorithms, including agentic artificial intelligence approaches, for the clinical integration