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for this position will be a highly motivated individual with experience in deep learning and medical imaging and a PhD degree in computer science, electrical and computer engineering, biomedical engineering
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manuscripts Preparation of grant applications Providing guidance to junior researchers Your profile: A PhD degree (or comparable) and a strong background in biostatistics, epidemiology, biology, medicine
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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to address cancer health disparities by integrating biological and behavioral aspects into their research. MENTORSBBOT mentors are all funded PIs with cancer- relevant extramural support. Mentors include PhDs
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are willing to conduct their research work in the US, at the Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA. Required Education, Experience and Skills Applicants must have a PhD
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. Responsibilities/Duties: · Perform biostatistics and bioinformatics for scRNA seq analysis. · Perform molecular, cellular, biochemical and immunological analyses · Optimize and troubleshoot experimental protocols
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contact Hong Zhu, Professor, at hzhu2m@virginia.edu. Minimum Requirements: Doctoral degree Preferred Qualifications: PhD in biostatistics, statistics, or a related quantitative field by the appointment
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to mentor graduate and undergraduate students within Dr. Donneyong’s research lab. Required Qualifications: A doctoral degree (PhD, ScD) in Pharmacoepidemiology, Epidemiology, Health Economics, Health
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Posted on Sat, 11/09/2024 - 11:35 Important Info Faculty Sponsor (Last, First Name): Gardner, Christopher Other Mentor(s) if Applicable: Clarke, Shoa, MD, PhD; Follis, Shawna, PhD, MS; Henriksen
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. Requirements Essential Requirements PhD Degree in a relevant scientific field (e.g. genetic epidemiology, molecular epidemiology, statistical genetics, biostatistics, health data science, etc) to be obtained max