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seeking to hire a Research Assistant (RA)/Technician. The candidate will join exciting projects developing experimentally-guided computational models to address unanswered questions related to natural and
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funding. KEY RESPONSIBILITIES A full-time Staff Associaate (Data Analyst II) for Molecular Medicine Learning Healthcare Program is needed to work under limited supervision of the Principal Investigators
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databases. Proficient in programming languages (Python or R). Experience with high-performance computing (Linux system) is preferred. Experience in conducting WGS and phylogenetic analysis is required. Strong
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. We use a combination of cutting-edge technologies, including comprehensive genomics and computational biology, genetic and transplantation-based cancer models, and real-time in vitro and in vivo
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the experimental system and test specific predictions of the models in the collected data. The ideal candidate will have expertise in visually guided behavior and strong computational skills, as well as superior
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Research Scientist to work at the interface between climate modeling and machine learning. The successful applicant will perform research as part of the multi-institution international project, M²LInES https
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with AI and Physics (LEAP), an NSF-funded Science and Technology Center at Columbia University. Responsibilities will include: Analyze data from observations and model simulations of extreme MHWs. Apply
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, coordination, and management of information and data, development and implementation of computer models and simulations, development of research materials (figures, presentations, papers, etc.) and work
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expertise in analyses of mouse models of cancer. - 30% e. Communication Must have excellent written communication skills, particularly the ability to clearly record data in written form or on a computer
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. The successful candidate will contribute to the development of computational models that describe interfacial reactions in electrochemical systems. Reactions at electrode?electrolyte interfaces and the resulting