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, computer vision in the Division of Health Data Science (HDS) at the DOS. The position is an annually renewable professional academic appointment. Duties/Responsibilities: ● Risk predictive model for clinical
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modeling, physiological signal analysis, and innovative neuromodulation strategies for neurological disorders such as epilepsy, chronic pain, and autonomic dysfunctions. Primary Responsibilities 35
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-tuning DNA sequence/genomic/omic large language models (gLLMs) with their applications to genetics, e.g. in identifying causal genes for Alzheimer’s disease (AD). You will have access to state-of-the-art
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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic
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, and publication of major results from the experiment. They will also lead the development of predictive distribution models that incorporate data from the experiment. The project is funded by the USGS C
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for recording across multiple cortical/ striatal circuits •Optogenetic and electrical real-time perturbations, including interventions directly related to clinical deep brain stimulation. •Parametric
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flux measurements using biogeochemical modeling. They will be responsible for managing projects related to field instrumentation and ecosystem flux modeling. 20% designing and implementing trace gas flux
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quality models to better understand the effect of soil health management practices on soil-water storage in agricultural fields. A postdoctoral position is available to examine the effect of soil health
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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neural populations and their application in animal models In the Department of Neurosurgery. There will be opportunities to lead a team of students, contribute to grant writing, engage in professional