machine vision and learning positions at Janelia Farms

[Ignacio Arganda-Carreras]

Maybe of interest for people in the list ;)

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The Branson Lab at Howard Hughes Medical Institute's Janelia Farm Research
Campus is seeking outstanding Postdoctoral Researchers and PhD Students to
develop new machine vision and learning algorithms for cutting-edge
neuroscience research. In particular, we are looking for computer
scientists with expertise in machine vision and learning interested in both
developing new algorithms as well as robust, usable systems that will
impact the field of neuroscience.

We are primarily a machine vision and learning lab, developing new
technologies for neuroscience research. We are focused on the problem of
jointly learning the vocabulary of animal behavior and its implementation
in the nervous system, in particular developing machine vision and learning
algorithms toward this goal. To do this, we are:
* Combining optogenetic/thermogenetic techniques to manipulate the activity
of neurons and new machine vision techniques for extracting the behavioral
effects of these manipulations from video and data mining techniques for
discovering the underlying structure.
* Jointly learning behavior-anatomy structure from video of animals
behaving and video of the neuronal activity (measured via calcium imaging).
The machine vision and learning systems we develop toward these goals are
general-purpose, and used by biologists across a variety of disciplines.

Relevant fields of machine vision and learning include:
* Learning-based pose estimation for high-resolution videos of animals
behaving.
* Fully and weakly supervised activity recognition.
* Multi-view clustering/structure discovery.
* Semi-supervised discovery of structure using a "human-in-the-loop"
learning paradigm.

The successful candidates for these positions will have:
* The creativity to develop new algorithms and learning paradigms for using
machine vision and learning for scientific discovery.
* Practical knowledge of the current state-of-the-art in machine vision and
learning.
* The commitment and dedication to develop robust, working systems.
* Interest in applications of computer science to biology, and the new
discoveries they enable.
* Strong programming expertise in MATLAB and C, C++, Java, or Python.

The application of machine vision and learning to large neuroscience video
data sets is an emerging field with great potential impact. New
technologies such as optogenetics, calcium imaging, and advances in
microscopy have enabled the collection of huge image data sets containing
detailed information about the structure and function of the nervous
system. Because of the scope and complexity of these data sets, machine
vision and learning are of vital importance in extracting scientific
understanding. The importance of this field of study has recently been
highlighted in Obama's BRAIN Initiative Report (
http://www.nih.gov/science/brain/2025/index.htm, Section II-4).

HHMI's Janelia Farm Research Campus is a pioneering research center near
Washington, D.C., where scientists from many disciplines, from computer
science to physics to neuroscience, develop and use emerging and innovative
technologies to pursue neuroscience's most challenging problems.
Established in 2006, Janelia was modeled after institutes like Bell Labs,
with small groups collaborating on high-risk, innovative, big science. All
research is internally funded by the Howard Hughes Medical Institute, and
salaries and benefits are highly competitive. Postdoc positions at Janelia
are renewable one-year appointments.

For more information about the Branson Lab, please visit:
http://www.janelia.org/lab/branson-lab .
For information about Janelia, please visit:
http://www.janelia.org/about-janelia .

Applicants should email a CV and a cover letter summarizing their research
experience and interests to Kristin Branson [hidden email].


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Ignacio Arganda-Carreras, Ph.D.
Seung's lab, 46-5065
Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology
43 Vassar St.
Cambridge, MA 02139
USA

Phone: [phone]
Website: http://bioweb.cnb.csic.es/~iarganda/index_EN.html

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