The Laboratory for Computational Vision (LCV), located within the Center for Neural Science at NYU, has openings for postdoctoral fellows in computational neuroscience, visual/auditory perception, and/or statistical image and signal processing. We're looking for creative scientists with an interest in developing, refining, and testing theories of sensory representation and processing. Applicants should have a PhD in a relevant technical field (e.g., electrical engineering, machine learning, statistics, physics, applied math), a flexible multi-disciplinary mindset, and a strong interest in the scientific study of the brain. Activities will include theoretical/computational exploration/simulation, and may also include an experimental component (human psychophysics, or animal physiology with one of our collaborators). Topics are to be negotiated, but some areas of current interest (with links to recent example publications) include:
• Density modeling and estimation for natural images
• Efficient coding of natural images in neural population responses: pub1, pub2
• Models for represention and perception of visual texture
• Hierarchical models for loss of information in the visual periphery
• Early visual models for perceptual distortion (along with perceptual testing of these models, and use in image processing, graphics, or computer vision)
• Representation of continuous transformations with discrete operators
• Invariance properties of hierarichal representations
• Integration of information across saccades
• Fitting "subunit" and/or gain control models to physiological data ( V1), ( retina)
• Modeling response variability in sensory neurons
• Modeling state-dependence of sensory responses
Interested? Send email to eero.simoncelli@nyu, including a CV in pdf format, name/email address of at least two references, and a brief description of: (1) your research/professional goals; (2) one or two research problems on which you've worked, and what you most liked (or disliked) about those experiences; (3) one or two problems on which you'd like to work, and a description of how you see them fitting into the research landscape of LCV.
Ad created: Jan 2016.