[Imageworld] 2 Post-doc and 1 Research Programmer Openings: Corso Group, CSE, SUNY at Buffalo

[Jason J. Corso]

Applications are invited for two-postdoctoral research associate
positions and one research programmer position in Professor Jason
Corso’s research group in Computer Science and Engineering at SUNY at
Buffalo.  The research area is object, event, and activity modeling,
learning and recognition in video.  The specific details of these
exciting projects are below.  More information can be found at
http://www.cse.buffalo.edu/~jcorso/job-openings.html

Post-Doc 1:  Semantic Video Summarization

The goal of the research project is to summarize the semantic content
in a video, requiring joint solution to semantic entity extraction
(i.e., object detection and tracking), entity-entity relationship
extraction, dynamic event recognition, and video categorization.
Learning of the models will be from massive collections of partly
labeled videos.

The successful candidate will be expected to make innovative
contributions to the research agenda in conjunction with the PI and
other project members.  The ideal candidate is a US Citizen with a
Ph.D. in computer science, applied mathematics/statistics, electrical
engineering, or equivalent, has a strong publishing record in
top-notch conferences and journals, has a strong understanding of
computer vision, machine learning, and knowledge
representation/ontologies, is an experienced programmer beyond Matlab,
and has experience with UNIX platforms.

This position is funded by an IC Postdoctoral Fellowship; see
http://www.icpostdoc.org/ for additional information.  The post-doc
will be joining a network of elite post-doctoral scholars doing work
related to the Intelligence Community and Department of Defense.  The
position is funded for three years and renewable on an annual basis
given adequate progress.  Salary is competitive and based on
experience and University policy.

Post-Doc 2:  Hierarchical Generative Object and Activity Modeling in Video

The goal of the research project to model person-person and
person-object interactions in video.  The research will involve
learning generative hierarchical models of objects and activities from
large unlabeled or partially labeled data collections; learning will
be conducted with a human-in-the-loop to provide domain semantics.
The probabilistic models of objects and activities will be grounded in
a domain ontology, which will guide both learning and inference by
providing high-level, symbolic reasoning.  Advances in statistical
inference will be required to support rapid activity recognition with
the generative models.

The successful candidate will join this major effort involving 5
senior investigators and 4 graduate students assistants and play a
critical role in making key research contributions.  The position is
open to all US and non-US citizens who hold a Ph.D. in computer
science, applied mathematics/statistics, electrical engineering, or
equivalent, have a strong publishing record in top-notch conferences
and journals, have a strong understanding of computer vision, machine
learning, and knowledge representation/ontologies, are experienced
programmer beyond Matlab, and have experience with UNIX platforms.
The position is funded for three years and renewable on an annual
basis given adequate progress. Salary is competitive and based on
experience and University policy.

Research Programmer

The research programmer will join a team of more than 10 researchers
conducting cutting-edge research in computer vision and machine
learning.  The primary emphasis is on high-level video analysis with
elements of semi-supervised machine learning, statistical inference,
and working with massive data.  The ideal candidate holds a BS (MS or
PhD preferred) in Computer Science or a related technical field.
Experience is preferred but not required.  S/he is a good communicator
and able to understand mathematical concepts and translate them into
source code.  S/he is experience in Matlab, Java, C/C++, including
JNI/JNA, Swing, Scientific Programming, and GPU development.  The
primary development platform is Unix (Darwin/BSD, Linux) and the
candidate must demonstrate familiarity with the platform.  The
position is funded for three years and renewable on an annual basis
given adequate progress. Salary is competitive and based on experience
and University policy.

Contact: Jason Corso      jcorso at buffalo.edu http://www.cse.buffalo.edu/~jcorso

Additional Information about SUNY at Buffalo and Corso’s Group

SUNY at Buffalo was founded in 1846 and is a member of the prestigious
Association of American Universities, ranking first among the nations
research-intensive public universities. UB serves to about 30,000
students, offers 84 Bachelor’s, 184 Master’s, and 78 Doctoral degrees.
 The Computer Science department at UB is among the oldest CS
departments nationwide, recently celebrating its 40th anniversary.
There are 29 faculty and 6 instructors in the department. The
department has a strong focus on computer vision, pattern recognition
and machine learning having 8 faculty in these areas.  Dr. Corso runs
a research group of 2 Post-docs, 7 Ph.D. Students, 6 Masters students
and 2 undergraduates.  He is PI on more than $3 million current
externally funded research projects all in the area of high-level
computer vision and learning.  His lab is 1250+ square feet with ample
computing resources, including an in-house Linux cluster, a 15TB SAN,
and connectivity to the 2000+ node Center for Computational Research
in downtown Buffalo.

--
Jason J. Corso, PhD
Assistant Professor
Computer Science and Engineering
SUNY at Buffalo

(o) 716-645-4754
(c) 716-208-3671
(e) jcorso at buffalo.edu
(w) http://www.cse.buffalo.edu/~jcorso