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Field
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Details Title Postdoctoral Fellow in Neurobiology (Ponce Lab) School Harvard Medical School Department/Area Neurobiology Position Description Postdoctoral fellow in visual neurophysiology and deep
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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Massachusetts. Specifically, this fellowship is focused on machine-assisted visualization. We welcome applications from recent PhD graduates who are interested in these or related fields, particularly those who
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; •Development of methodologies for integrated visualization in a 3D GIS environment; Phase 3 – Digital platform and 3D registry: •Creation of an interactive platform (webGIS or desktop) with visualization
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of the visual system. By broadening its focus, the program fosters interdisciplinary collaborations, driving significant advancements in understanding the complex, interconnected systems of the eye and beyond
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but not limited XPS, ICP-OES, GC-MS, TEM. Experience with data visualization and analysis software. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a
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of remote sensing imagery. Proficiency with GIS methods, applications, and visualization. Prior experience engaging with stakeholders and application of participatory methodologies. Background Investigation
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on visual attention models derived from eye-tracking data, building upon results obtained within the XAVIER project. The research fellow (holding an MSc degree) will be responsible for: Updating and testing
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visualization and model interpretability Personal Skills Self-initiative. Capacity to work independently and communicate efficiently. Strong problem-solving mindset. Strong writing skills. Strong interpersonal
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning