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Postdoc and staff positions in Advanced Neuro-Imaging & Technologies for Systems Neuroscience

Employer:  Rockefeller University
Job Number:  4019782
Date Posted:  03/02/2017
Application Deadline: Open Until Filled

Job Description

Postdoc and Staff Positions in Advanced Neuro-Imaging & Technologies for Systems Neuroscience

Laboratory of Neurotechnology & Biophysics
The Rockefeller University, New York, NY

Background: Over the last decade neuroscience has been revolutionizing our understanding of the brain. A major driver underlying this transformation has been the emergence of new optical technologies combined with advanced statistics and machine learning tools. Our lab has a major focus on development and application of advanced optical imaging technologies with applications for systems neuroscience.

What we do: We have pioneered optical techniques that allow near-simultaneous stimulation [1, 2] and functional imaging of neuronal activity on the whole-brain level at single-cell level in small model organisms [3, 4] and more recently in the more scattering rodent brain [5]. Thereby we are also for the first time in a unique position to discover the underlying principle of some of the most fundamental question about the brain: How does the brain represent sensory inputs? How does the spatiotemporal dynamics of neuronal population generate animal behavior? How does the brain make decision? We are developing appropriate technologies for addressing these questions in different model systems such as rodents and larval zebrafish

Positions: We are currently looking for several of highly motivated and ambitious candidates for the following projects:

•Development of new high-speed optical methods for large scale recoding of neuronal population activity
•Imaging in and through scattering media
•Development of computational imaging techniques
•Applications of quantum optics and ultrafast optical tools to biology

Depending on the specific project the ideal candidate should have the following profile:
- Highly motivated, ambitious and passionate about science
- PhD / Masters in physics, optical engineering, electrical engineering or systems neuroscience
- Experience with one and more of these areas would be highly desired: optics or optical modeling, ultra-fast laser systems, fiber optics, AMO physics/light matter interaction, RF electronics, craniotomy surgery, rodent behavioral experiments, large-scale data processing and cluster computing
- Basic programming skills (e.g. Matlab, Python, LabView)
- Highly result orientated, excellent time management and communication skills and the ability to effectively work in a team environment and willingness to work outside of the core expertise.

The successful candidates will join the lab at the Rockefeller University and will be embedded in our network of active collaborations in the New York area and beyond which are supported by dedicated recent awards. Interested candidates should send their CV including publications, copy of transcripts as well as the contact information of two references to Prof. Alipasha Vaziri (vaziriadmin@rockefeller.). For more information please visit our website www.vaziria.com or

1. Andrasfalvy, B., et al., Two-photon Single Cell Optogenetic Control of Neuronal Activity by Sculpted Light. PNAS, 2010. 107.
2. Losonczy, A., et al., Network mechanisms of theta related neuronal activity in hippocampal CA1 pyramidal neurons. Nature Neuroscience, 2010. 13(8): p. 967-72.
3. Schrodel, T., et al., Brain-wide 3D imaging of neuronal activity in Caenorhabditis elegans with sculpted light. Nature Methods, 2013. 10(10): p. 1013-1020.
4. Prevedel, R., et al., Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy. Nature Methods, 2014. 11(7): p. 727-730
5. Robert, R. et al., Fast volumetric calcium imaging across multiple cortical layers using sculpted light
Nature Methods, 2016 13, 1021-1028

Contact:  Alipasha Vaziri
Laboratory of Neurotechnology and Biophysics
Rockefeller University
1230 York Ave
New York, NY 10065
United States
Employer's Web Site:  Visit employer's website
Online Application: Apply for this job from Employer's website

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