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they help orchestrate the production and learning of dexterous movements. By gaining a better understanding of these fundamental mechanisms, our ultimate goal is to develop new therapeutic treatments
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equitable research environment that values diversity in all its forms. To learn more about ongoing research and recent publications, please visit: https://kaushiklab.com . Why MUN? The Faculty of Medicine
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | 5 days ago
fluorescence data. Developing machine learning methods to optimize data collection. In addition, the project is committed to developing open source tools that benefit the imaging community. The applicant will
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with collaborators through regular field and/or video-conference meetings.QUALIFICATIONS•Minimum qualifications are a PhD degree that is focused on forest ecology, wildfire ecology, silviculture
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Council of Canada). The research will focus on applying, developing, and implementing novel statistical methods for causal inference, integrative data analysis, and machine learning with large
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candidate should have a PhD in linguistics or a closely related discipline (such as psychology, computer science or speech science) by the position’s start date; excellent writing skills and publication
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: - To lead the computational part of a collaborative project on AI-assisted design of OPVs - To become knowledgeable in the field of OPVs and the relevant simulations - To learn relevant machine learning
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://www.schenlabuottawa.com/ Key Responsibilities: Lead a project that identifies the roles of specialized gene expression programs in distinct excitatory and inhibitory neuron subtypes during motor learning. Utilize in vivo
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skills for publication in top-tier journals and competitive grant applications. - Learning lab/research group management approaches. - Preparation of manuscripts for publications (including collaborative
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. Collaboration with other PhD students, postdocs, and senior researchers from the involved universities will allow us to integrate mathematical and physical models of the data to address the larger project goals