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individual will implement, simulate and analyze models of epileptic source localization from EEG signals. Collaborate with clinicians to obtain and analyze imaging, EEG, and outcome data. Prepare results
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background and interests and contact information only for at least three references to AcademicJobsOnline.org https://academicjobsonline.org/ajo/jobs/31488. ; We will begin to review applications on February
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. Individual will develop and test novel computational models of the neural activity generated by electrical stimulation of the brain. Also, perform data analysis utilizing medical imaging data, computer models
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Postdoctoral Researcher to work on projects related to digital holography and optical coherence tomography. Candidates should have a PhD in electrical or biomedical engineering or related disciplines with
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cancer and aging settings with CODEX multiplexed imaging. Required Qualifications at this Level Education/Training PhD Experience See job description for requirements. Skills See job description for
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scanning, analyzing data, presenting at conferences, and publishing papers, as well as helping PhD students with the same tasks. Approximately 70% effort will be dedicated to personal projects and 30
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. The successful applicant will possess a PhD or equivalent doctoral degree in engineering, material science, geoscience, environmental science, chemistry, industrial ecology, social science or another relevant
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cultured cells and animal models of skin diseases. Work Performed • Development of new and implementation and modification of existing experimental procedures. • Data preparation for oral presentations
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skills are particularly welcome. For information about the lab and the PI, please visit: https://www.cellbio.duke.edu/purushothama-rao-tata/ . This will be a minimum one-year appointment, contingent upon
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connections with other scholars and joining campus intellectual life, as well as mentorship from GSF faculty. Applicants should have PhD in hand by July 1, 2026, and should have earned their PhD no earlier than