Machine Learning List: Vol. 15, No. 3
Sunday, Feb 9, 2003
Contents
Calls for Papers and Other Meeting Announcements
CFP: IJCAI-03 Workshop - Style Analysis and Synthesis
AI EDAM Jnl CfP
2nd CFP for K-CAP '03: International Conference on Knowledge Capture
ICoBiCoBi 2003
CFP HMAS-03, 3rd Int. Wrkshp on Hybrid Methods for Adaptive Systems
IJCAI03 Wrkshp on Intelligent Techniques for Web Personalization
CFP:IJCAI03 Wrkshp on Learning Statistical Models from Relational Data
Career Opportunities
UCSD:tenure-track jobs ML, data mining, bioinformatics, e-commerce
Research Positions at SRI International
UtopiaCompression job announcement
Faculty position: Gatsby Computational Neuroscience Unit
Assistant Professor (C1) Open in Freiburg (Germany)
faculty positions at OGI School of Science and Engineering
The Machine Learning List is moderated. Contributions should be
relevant to the scientific study of machine learning. Please send
submissions for distribution to: [EMAIL PROTECTED] For requests to be
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[EMAIL PROTECTED]
In general, submissions should be no more than a few full-screens of
text. For meeting announcements, highlight the conference or workshop
web page and give a summary description of the goals of the event.
Information such as the list of program committee members, talk
schedules, and registration forms are unnecessary and should not be
included. Job adds are usually no more than a few full-screens so
they should fit naturally.
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From: "Shlomo Argamon" <[EMAIL PROTECTED]>
Subject: CFP: IJCAI-03 Workshop - Style Analysis and Synthesis
Date: Tue, 21 Jan 2003 09:48:36 -0600
Call For Papers
IJCAI 2003 Workshop
DOING IT WITH STYLE:
Computational Approaches to Style Analysis and Synthesis
August 10 2003, Acapulco, Mexico
Submission deadline: March 10, 2003
Website: http://ir.iit.edu/~argamon/style2003/
OVERVIEW
Style is an intuitive concept which may be roughly defined as the
'manner' in which something is done, as opposed to the 'content' of
what actually is being accomplished. In recent years a growing number
of researchers working in a variety of different areas have focused on
explicitly addressing recognition and generation of style in their
various disciplines, work that contrast with more traditional emphasis
on 'performance' or 'content' or 'meaning'. Indeed, in some media
such as music, visual art and to a lesser extent, film and even
expressive speech, 'meaning' itself comprises mainly factors such as
excitation and calmness or other emotional expressions that can be
considered aspects of style instead of what is usually thought of as
content.
We seek submissions that address all aspects of style analysis and
synthesis from a computational perspective, but are particularly
interested to see work that addresses some of the following questions:
- What is style, and how may it be formalized?
- What kinds of features indicate style (as opposed to function or
meaning)?
- How is style related to short- and long-term temporal
dependencies, such as found in music or text?
- How do stylistic features correlate with affect of the
observer/performer?
- How may style be effectively combined with pre-existing content?
- What sorts of formal modeling methods are useful in representing
style?
- How may one effectively learn a style of expression and then
execute it?
- How does perceived style depend on the observer's context?
- How may presentation style affect comprehension?
- What connections can be drawn from stylistic methods used for one
domain to another?
IMPORTANT DATES
(NOTE CHANGES!)
Submission deadline: March 10, 2003
Accept/reject notices sent: April 1, 2003
------------------------------
From: AIEDAM <[EMAIL PROTECTED]>
Subject: AI EDAM Jnl CfP
Date: Tue, 21 Jan 2003 15:53:51 -0500
AI EDAM Journal:
Artificial Intelligence for Engineering Design,
Analysis and Manufacturing
Special Issues Call for Papers:
Vol.18, No.5, November 2004
Learning and Creativity in Design
http://www.cs.wpi.edu/~aiedam/SpecialIssues/Duffy-Brazier.html
Papers due: 1st September 2003
------------------------------
From: John Gennari <[EMAIL PROTECTED]>
Subject: 2nd CFP for K-CAP '03: International Conference on Knowledge Capture
Date: Mon, 27 Jan 2003 12:11:40 -0800
C A L L F O R P A P E R S
Second International Conference on Knowledge Capture
K-CAP 2003
Sponsored by ACM SigArt
Oct 23-25th, 2003
Sundial Resort, Sanibel Island, Florida, USA
Submission deadline: April 28th, 2003
http://www.k-cap.org/
Information in all forms is increasingly available, but using it
effectively requires a range of technologies for representing,
manipulating, and reasoning with information. These technologies
comprise knowledge capture, the extraction of useful knowledge from
vast and diverse sources of information and raw data. Driven by the
demands for knowledge-based applications, and the unprecedented
availability of information on the Internet, the study of knowledge
capture has a renewed importance.
Although there has been considerable work in the area of knowledge
capture, activities have been distributed across several distinct
research communities, principally knowledge engineering, machine
learning, and natural-language processing. However, other fields study
knowledge capture, too. For example, in planning and process
management, mixed-initiative systems acquire knowledge about a user's
goals by taking commands or accepting advice regarding a task. In
addition, recent research with the Semantic Web includes work that
tries to capture the knowledge associated with appropriately annotated
web pages. All of these approaches are related in that they acquire
information and organize it in knowledge structures that can be used
for reasoning. They are complementary in that they use different
techniques and approaches to capture different forms of knowledge.
K-CAP 2003 will provide a forum in which to bring together disparate
research communities whose members are interested in efficiently
capturing knowledge from a variety of sources and in creating
representations that can be useful for reasoning. We solicit
high-quality research papers for publication and presentation at our
conference. Our aim is to promote multidisciplinary research that
could lead to a new generation of tools and methodologies for
knowledge capture.
Topics of interest include, but are not limited to:
** Knowledge acquisition tools
** Advice taking systems
** Authoring tools
** Learning apprentices
** Knowledge engineering and modeling methodologies
** Knowledge extraction systems
** Knowledge management environments
** Mixed-initiative decision-support tools
** Knowledge-based markup techniques
** Acquisition of problem-solving knowledge
SUBMISSION DEADLINE: April 28th, 2003
------------------------------
From: David Correa Martins Junior <[EMAIL PROTECTED]>
Subject: ICoBiCoBi 2003
Date: Tue, 28 Jan 2003 15:11:15 -0200 (EDT)
Call for Papers
ICoBiCoBi 2003
1st International Conference on Bioinformatics and Computational Biology
14-16 May 2003
Ribeir=E3o Preto, SP, Brazil
http://www.vision.ime.usp.br/~icobicobi/
As we move into the 21st century, the unprecedented possibilities for
multidisciplinary research in biology are posed to concentrate a great
deal of the attention and efforts in science and technology. The
promising perspectives include not only understanding and treating
diseases, but also deciphering the secrets of life from the molecular
to the environmental levels. At the same time, the vast complexity
underlying the biological systems represents a considerable obstacle
that will only be circumvented through the combination of powerful
mathematical concepts and methods, allied to the use of effective
computational implementation and simulation.
The 1st International Conference on Bioinformatics and Computational
Biology (ICoBiCoBi), to be held in Brazil from 14th to 16th May 2003,
represents a unique opportunity for bringing together under the
unifying theme of computer science a broad series of concepts,
problems and applications in biology. Special attention will be placed
on the combined use of concepts and techniques to address relevant
problems in biology.
Prospective authors are encouraged to submit manuscripts reporting
high quality and innovative approaches to bioinformatics and
computational biology. Every accepted manuscript will be published
electronically in the WWW and considered for subsequent publication,
in extended version, in print in the respective proceedings.
THEMES
Agronomy Drug Discovery
Genetics Data Mining
Computer Networks in Biology Biological Morphology
Developmental Biology Dynamical Systems
Molecular Engineering Complexity
Biophysics Neuroinformatics
Post-Genomics Statistics
Diagnosis Pattern Recognition
Gene Expression Networks Artificial Intelligence
Genetic Improvement Databases
Proteomics Parallel Computing
Optimization Software environments
------------------------------
From: "Andreas Nuernberger" <[EMAIL PROTECTED]>
Subject: CFP HMAS-03, 3rd Int. Wrkshp on Hybrid Methods for Adaptive Systems
Date: Tue, 28 Jan 2003 12:07:54 -0800
- Call for Papers -
3rd International Workshop on Hybrid Methods for Adaptive Systems
- HMAS 2003 -
Oulu, Finland, July 10-12, 2003
(Part of eunite 2003 symposium - http://www.eunite.org)
Following the success of the two preceding workshops on Hybrid Methods
for Adaptive Systems organised during the eunite symposia 2001 and
2002 we are pleased to announce that the third workshop is going to
take place during the eunite 2003 symposium July 10-12, 2003 in Oulu,
Finland.
The purpose of this workshop is to stimulate cross-community
discussion and to collect state-of-the-art contributions in the area
of hybrid methods. We are especially interested in contributions
discussing methods for the integration of fuzzy systems, neural
networks, evolutionary computation, machine learning and related
technologies and their application to adaptation in hybrid systems.
IMPORTANT DATES:
March 31, 2003 Deadline for submitting papers
April 21, 2003 Notification of acceptance
May 15, 2003 Deadline for submission of final papers
ADDITIONAL INFORMATION:
A list of topics of interest, guidelines for submissions, and
information about the conference site is available at
http://www.cs.berkeley.edu/~anuernb/hmas2003/
------------------------------
From: "Sarabjot Singh Anand" <[EMAIL PROTECTED]>
Subject: IJCAI03 Wrkshp on Intelligent Techniques for Web Personalization
Date: Wed, 29 Jan 2003 15:41:02 -0000
IJCAI 2003 Workshop on
Intelligent Techniques for Web Personalization
(ITWP '03)
Monday, August 11, 2003
Acapulco, Mexico
http://maya.cs.depaul.edu/~mobasher/itwp03/
OVERVIEW
The continued explosion in the amount of content and the number for
information sources available online is making the need for effective
personalized content delivery more acute. This has resulted in a renewed
interest in Web personalization as an indispensable tool for Web-based
organizations. Personalization can be defined as any action that tailors the
Web experience to a particular user, or set of users. The experience can be
something as casual as browsing a Web site or as (economically) significant
as trading stocks or purchasing a car. The actions can range from simply
making the presentation more pleasing to anticipating the needs of a user
and providing customized and relevant information. To achieve effective
personalization, organizations must rely on all available data, including
the usage and click-stream data (reflecting user behaviour), the site
content, the site structure, domain knowledge, as well as user demographics
and profiles. In addition, efficient and intelligent techniques are needed
to mine this data for actionable knowledge, and to effectively use the
discovered knowledge to enhance the users' Web experience. These techniques
must address important challenges emanating from the size and the
heterogeneous nature of the data itself, as well as the dynamic nature of
user interactions with Web sites, especially in e-commerce applications.
These challenges include the scalability of the personalization solutions,
data integration, and successful integration of techniques from machine
learning, information retrieval and filtering, databases, knowledge
representation, data mining, text mining, statistics, and human-computer
interaction.
TOPICS
Original contributions are solicited in the following areas:
- Data and Knowledge Modeling, Integration and Management
- Using domain knowledge for more effective personalization
- Data models for Web usage, content, and structure data
- Data integration across multiple channels
- Generation and updating of user profiles
- Cognitive models for Web navigation and e-commerce interactions
- The role of user context
- Enabling Technologies
- Machine learning and data mining in personalization
- Text mining techniques for content-based filtering
- Semantic Web mining
- Privacy preserving personalization
- Standards for data and knowledge modeling
- Quality of Service in Personalization
- Techniques for improving online data quality
- Evaluation of recommendation engines
- Metrics for personalization effectiveness
- Systems and Architectures
- Frameworks and systems for scalable collaborative filtering
- Agents for intelligent browsing and navigation
- Intelligent question answering systems
- Adaptive hypertext systems
- Hybrid Recommendation Systems
IMPORTANT DATES
Abstract Submission: February 28, 2003
Full Paper Submission: March 7, 2003
Notification of Acceptance: March 28, 2003
Camera Ready Papers Due: May 23, 2003
------------------------------
From: Lise Getoor <[EMAIL PROTECTED]>
Subject: CFP:IJCAI03 Wrkshp on Learning Statistical Models from Relational Data
Date: Fri, 31 Jan 2003 18:27:44 -0500
CFP: IJCAI-2003 Workshop
Learning Statistical Models from Relational Data
Monday, 11 August 2003
Acapulco, Mexico
http://kdl.cs.umass.edu/events/srl2003/
This workshop will explore approaches to learning statistical models
from relational data. The workshop will explore the foundations,
advantages, and limitations of the surprising array of approaches that
have been developed over the past decade. These include probabilistic
relational models, stochastic logic programs, Bayesian logic programs,
relational Bayesian networks, relational probability trees,
first-order Bayesian classifiers, relational Markov models, block
models and statistical relational models.
These techniques have been developed in several related, but
different, subareas of artificial intelligence (reasoning under
uncertainty, inductive logic programming, machine learning, and
knowledge discovery and data mining) and in some areas outside of AI
(e.g., databases and social network analysis). Most researchers only
have exposure to one or two techniques, and no clear understanding of
the relative advantages and limitations of different techniques has
yet emerged. We believe this is an ideal time for a workshop that
allows active researchers in this area to discuss and debate the
unique challenges of learning statistical models from relational data.
Potential topics include:
* Unique challenges of relational learning
* Representational power of different techniques
* Scalability of statistical relational model-building
* Alternative methods of incorporating background knowledge
* Inference and learning tasks for relational data (e.g., attribute
prediction, link prediction, consolidation, entity detection, object
identification and clustering)
* Learning statistical models from time-changing relational data
* Using statistical models to fuse relational information from noisy,
heterogeneous sources
* Contribution of ancillary steps to modeling (e.g., data cleaning,
transformation, and querying)
* Applications of relational models (e.g., social network analysis,
security and law enforcement, and analysis of hypertext collections)
This workshop is intended for researchers in the areas of machine
learning, knowledge discovery and data mining, information retrieval,
link analysis, and social network analysis.
IMPORTANT DATES
Mar 7, 2003 Submission deadline
Mar 21, 2003 Acceptance notification
May 16, 2003 Camera-ready version of papers
ADDITIONAL INFORMATION
See: http://kdl.cs.umass.edu/events/srl2003/
------------------------------
From: Charles Elkan <[EMAIL PROTECTED]>
Subject: UCSD:tenure-track jobs ML, data mining, bioinformatics, e-commerce
Date: Mon, 20 Jan 2003 17:06:31 -0800 (PST)
University of California, San Diego
Department of Computer Science and Engineering
Assistant/Associate/Full Professor
The Department of Computer Science and Engineering has several tenured
and tenure-track faculty positions open for Fall 2003. We invite
applications at all levels in all areas of computer science and
computer engineering. Areas of particular interest include
computational molecular biology and bioinformatics, graphics and
vision, machine learning and data mining, networking, security,
programming languages and compilers, software engineering, embedded
systems, computer architecture, e-commerce, algorithms as well as
storage systems and networks. However, excellent candidates in all
areas will be seriously considered.
The department is in a period of exciting growth and has attracted
extraordinary faculty in the past few years. It has excellent research
programs in computer science and computer engineering as well as a
strong interdisciplinary research program in computational biology and
bioinformatics. For more information, please consult our web page
http://www-cse.ucsd.edu.
The department is looking for applicants with outstanding research
credentials. Successful applicants are expected to lead a vigorous
research program and to have a strong commitment to teaching. A
Ph.D. in computer science or a related area is preferred. Salary and
rank will be commensurate with qualifications in conformance with
University of California policies.
We encourage candidates to send applications as soon as possible.
Positions remain open until filled.
Please send a letter of interest, curriculum vitae including research
interests and plans, the names and email addresses of at least four
references to the Recruiting Chair ([EMAIL PROTECTED]), and cite the
position reference number 4-102-AA.
------------------------------
From: "Karen L. Myers" <[EMAIL PROTECTED]>
Subject: Research Positions at SRI International
Date: Tue, 21 Jan 2003 13:54:56 -0800
Research Positions in AI at SRI International
The Representation and Reasoning group within the Artificial
Intelligence Center at SRI International is accepting applications for
the following two positions.
Computer Scientist -- We are looking for a research scientist with
interests and experience in one or more of the following areas:
agent-based systems, planning, learning, uncertainty. Initial
responsibilities will involve working with current staff on a range of
basic and applied research projects, with the expectation that the
hired individual will initiate their own research programs in the
longer term. Candidates are sought with strong technical skills,
breadth of knowledge within AI and Computer Science, research promise,
and team orientation. A Ph.D. in computer science or a related field
is required.
Research Engineer -- We are looking for an experienced programmer to
assist with the development of next-generation AI software tools and
applications related to reactive control, planning, and
scheduling. The ideal candidate will have broad familiarity with AI
and experience in developing AI technologies. Strong background with
a range of programming languages is desired, including Common Lisp,
Java, C, and C++. A B.S. or M.S. in computer science or related field
is required.
Artificial Intelligence Center at SRI International
SRI International is a not-for-profit research institute headquartered
in Menlo Park, California. SRI's Artificial Intelligence Center (AIC)
is one of the world's major centers for research in artificial
intelligence. Founded in 1966, the AIC has been a pioneer and a major
contributor to the development of computer capabilities for
intelligent behavior in complex situations.
The AIC focuses on comprehensive long-term research and development
programs in reasoning, natural language and speech understanding,
perception, and robotics. Its objectives are to understand the
computational principles underlying intelligence in man and machines
and to develop methods for building computer-based systems to solve
problems, to communicate with people, and to perceive and interact
with the physical world. The Center provides the stimulation and
creative exchange of ideas characteristic of an academic setting by
maintaining associations with universities and other research groups
and by providing opportunities for students and visiting fellows to
participate in ongoing projects.
The AIC maintains a staff of approximately 50 professionals,
supplemented by international visitors and students. Approximately 80%
of these professionals have a Ph.D., reflecting its commitment to
conducting basic research and developing ground-breaking
applications. Additional information about the AIC can be found at
http://www.ai.sri.com/.
APPLICATION PROCESS
Additional information on the above positions can be found at the
following websites.
Computer Scientist position:
http://sri.hrdpt.com/cgi-bin/c/highlightjob.cgi?jobID=4
Research Engineer position:
http://sri.hrdpt.com/cgi-bin/c/highlightjob.cgi?jobID=3
------------------------------
From: "Juhn Maing" <[EMAIL PROTECTED]>
Subject: UtopiaCompression job announcement
Date: Thu, 23 Jan 2003 14:06:56 -0800
Job Announcement - UtopiaCompression
Machine Learning/AI Scientist
UtopiaCompression is a dynamic and exciting high tech startup based in
Los Angeles, California. UtopiaCompression's vision is to become the
leader in intelligent imaging solutions by leveraging unique and
innovative approaches in the fields of image compression, image
understanding and related areas. We are delighted to be a 2002 winner
of the prestigious Advanced Technology Program (ATP) award of the
National Institute of Standards and Technology. With NIST funding,
UtopiaCompression will be developing a highly superior, disruptive,
conceptually-driven, intelligence-based image compression technology
radically different from current data driven linear transformation
based compression methodologies. Details on the award can be found at
http://www.atp.nist.gov/awards/00004936.htm
BASIC QUALIFICATIONS
UtopiaCompression is seeking highly qualified and skilled scientists
and professionals in artificial intelligence, machine learning,
imaging and pattern compression. Candidates are required to have
completed their Ph.D. in electrical engineering, computer science or
other related areas from a well recognized university. Post-doctoral
and industry experience with outstanding accomplishments and US
citizenship or permanent residency are preferred. Exceptional
candidates with M.A. degrees will also be considered.
SKILLS:
1 - In-depth knowledge and experience in statistical analysis,
reasoning and learning (e.g., Bayesian learning, estimation
maximization and maximum likelihood algorithms, and feature extraction
problems), (statistical) combinatorial optimization and learning
(e.g., simulated annealing, genetic programming), neural networks,
inductive and rule generation learning, fuzzy reasoning, (numeric)
decision tree learning, search methods, (image) data mining and
understanding, etc. Candidates are expected to have knowledge and
working experience in various learning regimes. For instance, in the
case of layered neural nets dexterous familiarity with the back
propagation algorithm, radial basis functions, etc., in decision tree
learning working experience in information gain measure, category
utility function, tree pruning, etc.
2 - Dexterous familiarity with various machine learning and
statistical software tools.
3 - Fluency in software analysis, design and development using C
programming environment. Candidates must be well versed and
experienced in C. Working experience in C++ (and Java) is a plus.
4 - Knowledge and working experience with image compression
techniques, and image analysis and processing is a big plus.
CONTACT
UtopiaCompression
Tel: 310-828-8777
Email: [EMAIL PROTECTED]
Email: [EMAIL PROTECTED]
Email: [EMAIL PROTECTED]
------------------------------
From: Peter Dayan <[EMAIL PROTECTED]>
Subject: Faculty position: Gatsby Computational Neuroscience Unit
Date: Mon, 3 Feb 2003 16:46:21 +0000
The Gatsby Computational Neuroscience Unit is looking to recruit a
lecturer (roughly equivalent to an assistant professor). We seek
someone with interests from across the range of theoretical
neuroscience and machine learning that would complement and bolster
our existing strengths in neural representation, neural computation,
and foundational and applied aspects of learning and Bayesian
statistics. There is also the opportunity to run a human psychophysics
lab in the service of testing theories. Remuneration will be at a
level appropriate to the international standing of the successful
candidate.
The Gatsby Unit was set up at University College London as a research
institute devoted to computational neuroscience and machine
learning. We have core funding for four faculty, five postdocs and
around ten PhD students. We have no undergraduate programme, so only
graduate-level teaching is required. We are located in Queen Square,
London, in close proximity to the Institutes of Neurology and
Cognitive Neuroscience and the Functional Imaging Lab, and also have
close ties with the Departments of Anatomy, Computer Science,
Psychology, Physiology and Statistics at UCL and with groups in
Physics and Experimental Psychology at Cambridge and beyond.
Applications, including a CV, a statement of research interests and
accomplishments and full contact details for three referees should be
sent by 14th March 2003 by email to Alexandra Boss at
[EMAIL PROTECTED], or by mail to her at Gatsby Computational
Neuroscience Unit, UCL, Alexandra House, 17 Queen Square, London WC1N
3AR, UK. For further information, please see www.gatsby.ucl.ac.uk or
contact Peter Dayan at [EMAIL PROTECTED]
------------------------------
From: "Luc De Raedt" <[EMAIL PROTECTED]>
Subject: Assistant Professor (C1) Open in Freiburg (Germany)
Date: Wed, 5 Feb 2003 19:36:52 +0100
The "Machine Learning and Natural Language Processing" lab has a
vacancy for a "Wissenschaftliche Assistenz (C1)"
This is a fixed-term (initially for 3 years, once renewable with
another 3 years) position at the post-doc/assistant professor
level. If a suitable candidate at the post-doctoral level cannot be
found, it can also be filled at the pre-doctoral level (BAT IIa).
The emphasis of the research in this lab lies on data mining, machine
learning, inductive logic programming, constraint based mining,
inductive databases, and their applications to bioinformatics.
The ideal candidate should have a good research record in one or more
of the above mentioned fields and have an interest in applying these
techniques to challenging scientific problems.=20
The University of Freiburg is an equal opportunity employer and
welcomes applications from women and minority candidates.
Freiburg is one of the most beautiful and attractive cities in
Germany, it lies at the foot of the Black Forest in the immediate
proximity of France and Switzerland.
Please contact:
Prof. Dr. Luc De Raedt
[EMAIL PROTECTED]
http://www.informatik.uni-freiburg.de/~ml
------------------------------
From: Melanie Mitchell <[EMAIL PROTECTED]>
Subject: faculty positions at OGI School of Science and Engineering
Date: Thu, 6 Feb 2003 11:45:25 -0800
Faculty Positions at the OGI School of Science and Engineering
The Department of Computer Science and Engineering invites
applications for faculty positions at all ranks. The current
strengths of our department include graphics and visualization,
adaptive systems and machine learning, databases and data mining,
networking, programming languages, software systems, human-computer
interaction, spoken language systems, software engineering, control,
computer architecture, image processing, and applied formal methods
and verification of both hardware and software. In addition to these
areas, our target areas for hiring include bioinformatics and
computational biology, security, mobile and embedded systems,
real-time and reactive systems, high-performance computing, vision,
robotics, and sensor fusion. While these are particular areas of
interest, we will consider outstanding candidates in any area of
computer science and engineering.
Building on a shared commitment to excellence in graduate education
and research, Oregon Graduate Institute of Science and Technology
(OGI) merged with Oregon Health Sciences University (OHSU) on July 1,
2001. OGI now is the OGI School of Science and Engineering in the
re-named Oregon Health & Science University (OHSU). The merger is
enabling the CSE department to expand in core disciplines and
establish strong interdisciplinary collaborations among researchers in
information technology, health care, biomedical engineering, and
environmental and biological sciences. Significant collaborations
between OGI and OHSU have existed for 30 years.
The typical teaching load in CSE is 2 graduate-level classes per
year. Faculty receive contracts of 2-5 years duration, renewable
annually with satisfactory academic performance. NSF, NIH and other
federal research sponsors recognize OGI faculty appointments as being
equivalent to tenured positions.
OGI is located 12 miles west of Portland, Oregon, in the heart of the
Silicon Forest. Portland's thriving high-tech community, extensive
cultural amenities and spectacular natural surroundings combine to
make the quality of life here extraordinary. To learn more about the
department, OGI, OHSU and Portland, please visit www.cse.ogi.edu.
To apply, send a brief description of your research interests, the
names of at least three references, and a curriculum vitae with a list
of publications to:
Chair, Recruiting Committee
Department of Computer Science and Engineering
OGI School of Science and Engineering at OHSU
20000 NW Walker Road
Beaverton, Oregon 97006
The email address for inquiries is:
[EMAIL PROTECTED]
OGI/OHSU is an Equal Opportunity/Affirmative Action employer. We
particularly welcome applications from women, minorities, and
individuals with disabilities.
------------------------------
End of ML-LIST Digest Vol 15, No. 3
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