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underwater acoustics and marine ecology. CMST pioneers innovative methods to monitor and manage marine environments. We measure, monitor, model, and predict anthropogenic noise. We are experts in sound
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
their impact on the tumor immune microenvironment and immunotherapy response. 3) Developing clinical-grade mechanism-driven AI models (iGenSig-AI) for predicting responses to targeted therapies and
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background in nonlinear optics, ultrafast photonics, and integrated photonics, alongside the ability to develop predictive models for optical materials and photonic devices. The successful candidate will work
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at the intersection of mathematics, computation, and cancer biology. We develop mechanistic, predictive models of cellular decision-making to address fundamental and translational challenges in cancer, including drug
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model predictions with biological knowledge and external data sources. Work closely with academic partner groups and the Innovation & Business (I&B) team to align technical development with biological
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experimental testing of the predictions from the computational model of religious decision-making in cooperation with the Principal Investigator, Dr. Martin Lang and another postdoctoral researcher with skills
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transcriptomics and multi‑omics data. You will also partner with AI experts to integrate predictive models and advanced analytics into omics workflows. You will work in an expanding team led by Dr. Masoomeh
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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Actionable Data for Opioid Response in KY (RADOR-KY) project. This position will build data science solutions and predictive models for time series forecasting systems related to risk prediction, outcome
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, the work seeks to establish predictive fingerprints of metal-ion mobility and uncover general principles linking structure, bonding, and dynamics. Particular emphasis will be placed on understanding both