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Medical Center, the Herbert Irving Comprehensive Cancer Center, the Irving Institute for Cancer Dynamics, the New York Structural Biology Center, the New York Genome Center, and the Columbia Data Science
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the following document(s): A letter of motivation describing your interests, experience and motivation to join the team A curriculum vitae including a list of publications Contact information for two references
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to applicants who have received their Ph.D. degrees in neuroscience or related fields within the last 3 years and have experience in imaging in vivo. Skills in computational neuroscience and data mining using
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, regardless of their role, receive the resources, support, and encouragement to advance and grow their careers. The Sr Clinical Research Associate is responsible for performing data abstraction, collection, and
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experiments, observational studies, data synthesis and modeling. We focus on mutualistic and antagonistic interactions of insects and spiders with other organisms, and are particularly interested in temporal
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parameters, sediment and soil nutrients (especially carbon and phosphorus), and measurements of greenhouse gas dynamics. Experience in handling and analyzing large and continuous data sets covering a broad
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(e.g. R, Python) and an ability to work with large datasets Strong record of peer-reviewed publications Ability to independently design and execute experiments and interpret data Ability to work in a
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advanced techniques such as CRISPR/Cas9 gene editing, protein biochemistry, mass spectrometry, and live-cell imaging. Analyze data, interpret results, and present findings at internal and external scientific
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or requirements, and any other information relevant or helpful for us to consider. Curriculum Vitae: Please include a list of your peer-reviewed publications, any major prize/award and patents. If you have been
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
and fastest-growing fishery in the Southern Ocean, regulated by the CCAMLR, which aims to manage the fishery sustainably, relying on ecosystem-based approaches incorporating data on predator populations