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related to battery materials, correlated electron calculations, including via DFT+U, supercells, dynamical mean field theory or experience in defect and/or alloy calculations, machine learning, and other
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with a PhD in computer science or bioinformatics are encouraged to apply. We create statistical, machine learning, and deep learning approaches for the processing of this data, with a major focus on
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neuroimaging and fluid biomarkers, (b) systems biology analysis of pathways from multi-omics data using multi-layered network approaches, © machine learning for identification of genetic risk factors in ADRD, (d
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neuroimaging and fluid biomarkers, (b) systems biology analysis of pathways from multi-omics data using multi-layered network approaches, © machine learning for identification of genetic risk factors in ADRD, (d
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Qualifications Experience with machine learning and AI models. Ability to communicate clearly with colleagues, Data presentations Scientific publication experience Special Instructions Priority Application Review
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. Department Contact for Questions Miranda Lockwood, SHRM-CP Human Resources Business Partner mjlockwo@iu.edu Additional Qualifications Experience with machine learning and AI models. Ability to communicate
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monitoring in rodents, and neurobehavioral testing panels. The postdoctoral fellow is expected to independently plan and conduct experiments under the guidance of the PI, using molecular and cellular biology
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monitoring in rodents, and neurobehavioral testing panels. The postdoctoral fellow is expected to independently plan and conduct experiments under the guidance of the PI, using molecular and cellular biology
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Chronic Conditions (ADACC) Network. This consortium will consist of multidisciplinary investigators dedicated to developing evidence-based strategies for the use and implementation of biomarkers
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pathology on computational, molecular, cellular, preclinical and translational levels. A spectrum of scientific methods includes state-of-the-art multi-omics approaches, machine learning and implementation