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experimentalists (such as wet lab biologists); the collaborative mindset (including the willingness to undergo and provide code review); the commitment to open science and reproducibility (including the willingness
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of submission, Mitacs will contact participants about the outcome of the application. Travel must take place within a year from the date of the outcome. The intern provides the completed Mitacs Code of Conduct
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of your name and the code “Postdoc_PB3_25.1” (e.g. “Max_Mustermann_Postdoc_PB3_25.1”). The application deadline is the 15th of June, 2025, 23:59:59. Unfortunately, application expenses cannot be reimbursed
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of manuscripts for publication in high-impact journals and conferences; Create, maintain, and document high-quality research code for reproducibility; and Collaborate with scientists within the NYU Global Network
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the project include mathematical derivation, analysis, and comparison of models, methods, and simulation approaches; rapid prototyping of new ideas in custom code; implementation of new models, methods, and
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of the ‘population code’, gaining a causal understanding of how population activity drives actions. The postdoc will work with the PI to develop an independent project, that leverages the expertise of the lab and the
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superb quantitative background, strong coding skills (e.g., Python, R), expertise in infectious disease modeling across multiple pathogens, expertise with large datasets and statistical analysis, and high
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; etc. • Data management: Ability to clean, code and store information to increase anonymity and confidentiality • Data analysis: this position will have a primary focus on qualitative data, such as
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. Selection Process Received applications will be considered carefully in line with principles of the EU Charter and Code for Researchers . Selection criteria: (i) meeting qualification requirements described
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survival surgery, two-photon microscopy and analysis, patch-clamp, intracranial EEG monitoring and analysis, optogenetic techniques, mouse models of epilepsy. Coding skills (Python). Baylor College