55 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at Duke University
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collaborative environment at Duke is ideal for our multi-scale modeling research efforts. An earned PhD and previous experience in computational neurostimulation modeling are required as are excellent
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and dynamic wave propagation, in particular: (i) developing domain decomposition methods, (ii) damage models, (iii) nonlinear mechanics. 2) Validate the model by performing simulations using
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& Behavioral Sciences at Duke University School of Medicine. Our research combines laboratory behavioral pharmacology, ecological momentary assessment, and functional neuroimaging to examine neurobehavioral
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differentiation and melanoma and multiple myeloma biology utilizing cultured cells and animal models of skin diseases. Work Performed • Development of new and implementation and modification of existing
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Activities: Research Topic: Bioengineered Human Tissue Model for Juvenile Dermatomyositis Job Description: Our lab is focused on using bioengineered human muscle systems (myobundles) to research rare pediatric
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tenure-track faculty members, 1250 undergraduate students, 1400 master’s students, and 600 PhD students. Housed within a university renowned for its programs in the liberal arts, medicine, business and law
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, and to interact regularly with Dr. Jonathan Campbell to design and execute experimental studies involving animal and cell-based models of metabolic disease. In addition, will also perform the following
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implement computational models and perform deep learning analyses for the early detection of Alzheimer’s disease using MRI, biomarkers, and advanced computational techniques · Collaborate with a
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. Minimum Requirements: The position requires a PhD in biological sciences, chemistry, or a related discipline and a strong record of publications in peer-reviewed journals. Preferred Qualifications: Ideal
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restoration of function. The successful applicant will combine computational modeling, engineering optimization, and in vivo experiments to advance understanding and application of electrical block of neural