[visionlist] Real World Eye Tracking Course


[visionlist] Faculty position, University of California Irvine

University of California, Irvine 

Faculty Position in Functional MRI Methods

The Department of Cognitive Sciences (http://ift.tt/1xQLdfh) at the University of California, Irvine (UCI) is seeking applicants for an assistant or early associate professor tenure-track position in functional MRI (fMRI) methods with cognitive neuroscience applications. The successful candidate will participate in the management of a new 3T MRI facility to be housed in the School of Social Sciences and in a campuswide effort to develop multimodal neuroimaging facilities. We seek candidates who combine a strong research program in fMRI methods (e.g., pulse sequence development, hardware development, or innovation in signal analysis) with an interest and record of research in one or more areas of cognitive neuroscience.

The successful candidate will be expected to establish an independent research program, and interact with a large and diverse group of scientists at UCI interested in brain and cognitive sciences.

Interested candidates should apply online at: http://ift.tt/1UfxEvV. To ensure full consideration, applications should be completed by February 15, 2016.

The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.


[visionlist] Jobs: 2 Visiting Assistant Professor Positions- College of Wooster

The Department of Psychology at The College of Wooster seeks two visiting Assistant Professors for the 2016-2017 academic year beginning August 2016. 

A two-semester load consists of five regular courses and mentoring senior research, equivalent to a sixth course. Preference given to candidates who can teach statistics. In addition, we seek experimental psychologists to teach some of the following courses:
introduction to neuroscience, or memory and cognition, social psychology, psychology of women and gender, environmental psychology, personality psychology, child and adolescent psychology. Ph.D. by appointment date preferred. A strong program of research and
a commitment to undergraduate teaching are necessary. Employment is subject to federal laws requiring verification of identity and legal right to work in the United States as required by the Immigration Reform and Control Act. Please contact Amber Garcia,
Chair of Department of Psychology and Search Committee Chair with specific questions Professor
Amber Garcia. Review of applications will begin January 15, 2016.

A complete application will include: a letter of application, CV, statements of teaching and research interests, three letters of recommendation, and any evidence of scholarship and teaching skills, including course evaluations if available.  Apply through
the Interfolio link below. Interfolio accounts are free to applicants – simply press “apply.”

Apply at:
http://ift.tt/1Sl7wRJ

___________________________

John G. Neuhoff

Department of Psychology

The College of Wooster

http://jneuhoff.com


[visionlist] Fruit Fly Brain Hackathon

Fruit Fly Brain Hackathon 2016

FFBH 2016

March 17, 2016

Columbia University, New York, NY 10027

The goal of the hackathon is to bring together researchers interested in developing executable models of the fruit fly brain. Towards that end we will engage systems and computational neuroscientists in modeling, design, implementation and biological validation of an open-source emulation platform of the whole fruit fly brain. All hackathon participants will be provided with an Amazon Machine Image of the recently developed open-source Neurokernel platform for executable fruit fly brain circuits.

The hackathon is aimed at three main groups of participants: biologists, modelers and software engineers. For biologists, the hackathon focuses on the intuitive modeling and representation of biological data, such as anatomical and recordings data of the fruit fly brain, in the NeuroArch database. For modelers, the hackathon aims at creating/modifying models of neuropils that are compliant with the Neurokernel API. For software engineers, the hackathon focuses on improving the Neurokernel platform and its API, and developing new, proof-of-concept features that are needed by biologists and modelers alike. All hackathon participants will be strongly encouraged to collaborate towards the realization of executable fruit fly brain models.

The Fruit Fly Brain Hackathon is organized in conjunction with the Columbia Workshop on Brain Circuit, Memory and Computation on March 18-19, 2016. Participants of the hackathon are welcome to attend the workshop.

Registration is free but all participants have to register (http://ift.tt/22wwvpU).

Organizers:Paul Richmond, Department of Computer Science, University of Sheffield Adam Tomkins, Department of Automatic Control and Systems Engineering, University of Sheffield Nikul Ukani, Department of Electrical Engineering, Columbia University Yiyin Zhou, Department of Electrical Engineering, Columbia University 

More information can be found on the hackathon website:http://ift.tt/1YPWhki


[visionlist] NETI workshop at UT Austin

NETI 2016
The Center for Perceptual Systems at the University of Texas at Austin is
hosting a workshop on “Natural Environments, Tasks and Intelligence”
(http://ift.tt/1MDEDZO).

Dates:  April 15 – 17, 2016 (Friday – Sunday)
Purpose:  Perceptual and motor systems must reflect the natural tasks the
organism performs as well as the properties of the natural environments in
which the organism performs those tasks. Thus, the aim of this workshop is to
stimulate research in “natural systems analysis,” which consists of
several interrelated components: (i) identification and characterization of
natural tasks, (ii) measurement and analysis of natural scene statistics, (iii)
analysis of the computational requirements of natural tasks, (iv) rigorous
experimental study of neural and behavioral performance in natural tasks.

Organizers: Bill Geisler, Mary Hayhoe, and Dana Ballard
Speakers:

 

Richard
Anderson       Division of Biology and
Biological Engineering, CalTech

Matthias
Bethge        Center for Integrative
Neuroscience, Universität Tübingen

Emily
Cooper               Computational
Vision Group, Dartmouth University

Lawrence
Cormack    University of Texas at Austin

Peter Dayan                Gatsby
Computational Neuroscience Unit, UCL

Greg
DeAngelis          Brain and Cognitive
Sciences, University of Rochester

Jim Dicarlo                   McGovern
Institute of Brain Research, MIT

Alex Huk                       University
of Texas at Austin

Richard
Murray          Centre for Vision
Research, York University

Peter Neri                    Laboratoire
des Systèmes Perceptifs, Ecole Normale Supérieure

Nicholas
Priebe           University of Texas at
Austin

Eyal
Seidemann          University of Texas at
Austin

Eero
Simoncelli           Center for Neural
Science, NYU

Stephan
Treue            Department of Cognitive
Neurosciences, University of Göttingen

Jochen
Triesch             Frankfurt Institute for Advanced Studies, J.W. Goethe
University

In addition to the oral presentations there will also be a poster session
Saturday afternoon. Potential attendees are encouraged to register in advance
as the size of the workshop will be restricted to foster interaction among
attendees.
Spring in Austin is a glorious time of year with wildflowers in bloom and an
average temperature ranging from 57 F (14 C) low to 79 F (26 C) high.


[visionlist] PhD Studentship – University of East Anglia


[visionlist] Research in Biological and Machine Intelligence at Carnegie Mellon University

A Research Project in Biological and Machine Intelligence at Carnegie Mellon
University

Researchers at Carnegie Mellon University, in collaboration with
researchers at multiple universities, including Johns Hopkins University, the
University of Pittsburgh, the University of North Carolina are launching an inter-disciplinary
collaborative research program in Biological and Machine Intelligence to study
the neural mechanisms of visual intelligence and learning in the brain.  The general objective is to develop new biologically inspired or
constrained  machine learning and artificial intelligence systems.  The current collaborative project will involve the
following five areas of research: (1) neurally constrained machine learning and
vision theory, (2) computational vision and mathematical neural circuit modeling,
(3) large-scale calcium imaging in mice, (4) large scale multi-electrode
electrophysiology in primates, and (5) advanced neural big data analysis.  The current  project is focused on
the study of perceptual learning and inference mechanisms in the mammalian
visual cortex in the theoretical framework of compositional theory and
probabilistic graphical models. We are recruiting postdocs and graduate
students with interests and/or expertise in each of the above five areas of research.
Participating faculty involved in the current  project  include:

Tai Sing Lee (Project director, CMU,
Computer Science and and Center for the Neural Basis of Cognition (CNBC), tai@cs.cmu.edu )

Sandra Kuhlman (CMU, Biological Science
and CNBC, skuhlman@andrew.cmu.edu)

Alan Yuille (Johns Hopkins, Center for
Cognition, Vision and Learning, alan.l.yuille@gmail.com)

Steve Chase (CMU, Biomedical Engineering
and CNBC),  schase@cmu.edu )

Brent Doiron  (University of Pittsburgh, Mathematics and
CNBC,  bdoiron@pitt.edu )  

Abhinav Gupta (CMU, Robotics, abhinavg@cs.cmu.edu )

Robert Kass (CMU, Statistics and CNBC, kass@andrew.cmu.edu)

Gary Miller (CMU, Computer Science, glmiller@cs.cmu.edu )

Ruslan Salakhutdinov (CMU, Machine
Learning, rsalakhu@cs.toronto.edu )

Spencer Smith (University of North
Carolina, Cell biology and Physiology, slab@email.unc.edu
)

Byron Yu  (CMU,
Electrical Engineering and CNBC, byronyu@cmu.edu
).

Applicants should have strong
interest or background in neuroscience. Desired background and expertise
includes one or more of the following: neurophysiology, preferably with background
in mice or primate experiments,  computer science/engineering/physics
with an interest or experience in modeling neural circuits, development of bio-inspired
computer vision and machine learning systems, or application of statistical and machine learning techniques to large-scale neural data analysis. Interested
postdoc applicants should send their CV, and research and career interest
statements to aibrain@cmu.edu AND the
specific participating faculty member(s) whom they are interested in working with. We
will review applications on a rolling  basis. Most hiring decision will be decided by the end of February 2016. Most