64 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at Duke University
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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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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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[map ] Subject Areas: Environmental Analysis Climate Science Ecology Environmental Management Geosciences or Atmospheric Sciences (more...) Environmental Science Appl Deadline: (posted 2024/12/02
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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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and non-invasive neurostimulation. The strong interdisciplinary and collaborative environment at Duke is ideal for our multi-scale modeling research efforts. An earned PhD and previous experience in
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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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. 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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cells with organoid culture, which will create novel pre-clinical disease models. 3.Identifying vulnerabilities in treatment-resistant epithelial cancers. 4.Developing novel therapies targeting oncogenic
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mathematics and engineering. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit and state
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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