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are looking for a qualified Postdoctoral Research Associate with interests in various applied mathematical models, particularly arising from solid/fluid mechanics, biostatistics, and opinion dynamics, as
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experience working with laboratory animals, including animal injection, collection and processing of animal tissues and biological fluids; and analyses of these samples. The candidate should be able to design
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 7 days ago
and aerodynamics through the use of comprehensive analysis, high-order computational fluid dynamics (CFD), and direct numerical simulation (DNS) tools. The postdoctoral researcher will work with CAMRAD
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disease and stroke using novel and integrative computational and statistical analyses. The candidate will hold a PhD in statistics, Bioinformatics, Computational Biology, Biostatistics, Statistical Genetics
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hold, or shortly expects to obtain, a PhD qualification in Genetics, Bioinformatics, Computer science, Data science, Statistical Genomics or a related discipline involving the interrogation of ‘omics
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Engineering, Electrochemistry Qualifications and Education Level: Applicants must have a PhD on the topics related to the call. Skills: Previous expertise in material science applied to environmental
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, imaging, biomarkers distribution in blood or synovial fluid) as well as histological evaluation of multiple tissues (cartilage, bone, synovium, muscles), protein/gene expression analyses in isolated tissues
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organize group meetings, co-mentor graduate and undergraduate students, and publish high-impact scientific journal articles and conference papers. Minimum Qualifications: PhD in Mechanical Engineering
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and Geophysics. Candidates should have a PhD in geology, geophysics or related field by the time of this appointment, be within 5 years of their PhD and have not held a permanent or tenured faculty
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bridges the gap between static structural snapshots and the fluid, dynamic nature of the cellular landscape, providing a holistic view of how metabolic sensors operate within their native membrane