8 post-doc-machine-learning Postdoctoral positions at University of Southern California
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translational research involving multimodal neuroimaging analyses, statistics, machine learning, and/or glucose metabolism are preferred. Education and Experience Requirements: PhD in neuroscience
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, reinforcement learning, and/or wireless communications. The candidate should hold a doctoral degree in electrical or computer engineering or related fields. The successful candidate will have a strong publication
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degree in industrial engineering, operations research, statistics, or machine learning and have a strong research record. • Qualified candidates should have prior research and publications in optimization
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desirable, but not necessary. Experience in conducting genetic epidemiologic research and analyzing large genetic datasets is also a plus, but not necessary. Passion to learn about human genetic research and
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candidate will have the desire to conduct research, learn new technologies, be able to analyze and interpret results of complex experiments on real systems and to publish these results in peer-reviewed
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genetic approaches to understand the post-transcriptional gene regulatory mechanisms in cardiovascular development, regeneration, and diseases. The position is for qualified candidates who wish to pursue a
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, and/or molecular biology. Interested candidates should send their CV and a list of three references to Dillon Cogan at dcogan@usc.edu. The annual salary for this position is $68,640. When extending
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the following materials: Cover letter (1 page) Curriculum Vitae Research proposal (up to 2 pages) Names and e-mail addresses of 3 references Consideration of applications and nominations will continue until