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Today's Topics:
1. PhD Candidate 'Parameterized complexity of approximate
Bayesian inferences' (Bodlaender, H.L. (Hans))
2. CFP: IPDPS ParSocial 2017 Workshop - 2nd IEEE Workshop on
Parallel and Distributed Processing for Computational Social
Systems (John Korah)
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Message: 1
Date: Wed, 7 Dec 2016 16:03:02 +0000
From: "Bodlaender, H.L. (Hans)" <H.L.Bodlaender@uu.nl>
To: "DMANET@zpr.uni-koeln.de" <DMANET@zpr.uni-koeln.de>
Subject: [DMANET] PhD Candidate 'Parameterized complexity of
approximate Bayesian inferences'
Message-ID:
<998083673200E4428DA4552D14ED58E34DDADEAC@WP0047.soliscom.uu.nl>
Content-Type: text/plain; charset="Windows-1252"
PhD Candidate 'Parameterized complexity of approximate Bayesian inferences' (1.0 FTE)
Faculty of Social Sciences, U. Nijmegen, the Netherlands
Vacancy number: 24.49.16
Application deadline: 1 February 2017
Responsibilities
The recent Predictive Processing account in neuroscience postulates that the brain continuously predicts its future inputs, using generative models relating hypothesized causes to perceived effects. It entails that the brain actually implements some form of approximate Bayesian inference, combining prior expectations with newly arriving information to make sense of its inputs. Bayesian computations, however, are computationally intractable for situations of real-world complexity, even when approximated. This is in marked contrast to the efficiency of inference and learning as done by the brain in practice. The objective of this project is to resolve this paradox by studying the fundamental properties of approximate Bayesian inferences. The vital question we seek to answer is 'under what biologically plausible situational constraints can approximate Bayesian inference be rendered tractable?' The approach we use to address this question is the mathematical theory of parameterized complexity analysis, algorithm design, and computer simulation.
You will explore the boundaries between tractable and intractable (parameterized) sampling algorithms, contribute to the mathematical tools to assess such algorithms, and analyse the computations postulated in the Predictive Processing account. You will also contribute to our Artificial Intelligence educational programme, in particular by supervision of student projects and assistance in lab courses. In addition, you will be eligible to follow courses at the IPA and SIKS research schools. You will be part of the Donders Graduate School for Cognitive Neuroscience.
Work environment
The Donders Institute for Brain, Cognition and Behaviour focuses on state-of-the-art cognitive neuroscience, using a multidisciplinary approach, and offers excellent lab and neuroimaging facilities, PhD supervision and courses, and technical support.
The project is embedded in the Donders research theme "Perception, Action and Control" and will be supervised by Dr Johan Kwisthout. You will join the Computational Cognitive Science research group, headed by Dr Iris van Rooij, at the Donders Centre for Cognition (DCC). The DCC is part of the Faculty of Social Sciences, one of the largest faculties at Radboud University in Nijmegen. The institute offers excellent research facilities and study programmes that rank among the best in the Netherlands. The candidate will also maintain regular research contacts with the Algorithms and Complexity group, headed by Prof. Hans Bodlaender, at the Department of Information and Computing Sciences at Utrecht University.
The Donders Institute is an equal opportunity employer, committed to building a culturally diverse intellectual community, and as such encourages applications from women and minorities. The Radboud University offers a parental leave scheme and day care on campus.
What we expect from you
an MSc degree in computer science, mathematics, artificial intelligence, cognitive science, cognitive neuroscience, or a related field;
strong motivation to conduct a conceptually challenging theoretical research project in a highly interdisciplinary context;
you have strong formal and analytical skills and are fascinated by the foundations of computation as well as how the brain actually realizes computations;
knowledge of parameterized complexity theory and/or Bayesian networks would be a strong bonus.
What we have to offer
employment: 1.0 FTE;
in addition to the salary: an 8% holiday allowance and an 8.3% end-of-year bonus;
the gross starting salary amounts to €2,191 per month, and will increase to €2,801 in the fourth year;
you will be appointed for an initial period of 18 months, after which your performance will be evaluated. If the evaluation is positive, the contract will be extended by 2.5 years;
this PhD position at the Donders Centre for Cognition is a 0.9 FTE research and 0.1 FTE teaching appointment;
you will be classified as a PhD Candidate (promovendus) in the Dutch university job-ranking system (UFO).
Other Information
The intended start date of the project is April 2017.
For more information about this vacancy, please contact:
Dr. Johan Kwisthout, project leader
Telephone: +31 24 3655977
E-mail: j.kwisthout@donders.ru.nl
Are you interested?
You should upload your application (attn. of Dr. Johan Kwisthout) exclusively our vacancy website: http://www.ru.nl/werken/details/details_vacature_0/?recid=593059# Your application should include (and be limited to) the following attachment(s):
Cover letter
CV, including two references
list of grades
Please make sure that all documents are in English.
------------------------------
Message: 2
Date: Wed, 7 Dec 2016 11:16:08 -0600
From: John Korah <john.korah@gmail.com>
To: dmanet@zpr.uni-koeln.de
Subject: [DMANET] CFP: IPDPS ParSocial 2017 Workshop - 2nd IEEE
Workshop on Parallel and Distributed Processing for Computational
Social Systems
Message-ID:
<CAHp7Y_f8YQpqqY6YwHGWcxvb4GH4TAQOER3YhWe9pMOH-8kPiA@mail.gmail.com>
Content-Type: text/plain; charset=UTF-8
###############################################################################
CALL FOR PAPERS
The 2nd IEEE Workshop on Parallel and Distributed Processing for
Computational Social Systems
June 2 2017, Orlando, Florida USA.
Conference Website : http://www.lcid.cs.iit.edu/parsocial
(In conjunction with IEEE International Parallel & Distributed Processing
Symposium (IPDPS))
IMPORTANT DATES
Paper submission deadline : January 16, 2017
Notification of acceptance : February 27, 2017
Camera-ready papers : March 13, 2017
Workshop : June 2, 2017
################################################################################
ABOUT PARSOCIAL
Computational methods to represent, model and analyze problems using social
information have come a long way in the last decade. Computational methods,
such as social network analysis, have provided exciting insights into how
social information can be utilized to better understand social processes,
and model the evolution of social systems over time. We have also seen a
rapid proliferation of sensor technologies, such as smartphones and medical
sensors, for collecting a wide variety of social data, much of it in real
time. Meanwhile, the emergence of parallel architectures, in the form of
multi-core/many-core processors, and distributed platforms, such as
MapReduce, have provided new approaches for large-scale modeling and
simulation, and new tools for analysis. These two trends have dramatically
broadened the scope of computational social systems research, and are
enabling researchers to tackle new challenges. These challenges include
modeling of real world scenarios with dynamic and real-time data, and
formulating rigorous computational frameworks to embed social and
behavioral theories. The IEEE Workshop on Parallel and Distributed
Processing for Computational Social Systems (ParSocial) provides a platform
to bring together interdisciplinary researchers from areas, such as
computer science, social sciences, applied mathematics and computer
engineering, to showcase innovative research in computational social
systems that leverage the emerging trends in parallel and distributed
processing, computational modeling, and high performance computing.
The papers selected for ParSocial will be published in the workshop
proceedings. Proceedings of the workshops are distributed at the conference
and are submitted for inclusion in the IEEE Xplore Digital Library after
the conference.
CALL FOR PAPERS
Areas of research interests and domains of applications include, but are
NOT LIMITED to:
*Large-Scale Modeling and Simulation for Social Systems*
Social network based models
Models of social interactions (e.g. influence spread, group formation,
group stability, and social resilience)
Complex Adaptive System (CAS) models (e.g. modeling emergence in social
systems)
Models incorporating socio-cultural factors
Novel agent based social modeling and simulation
Modeling with uncertain, incomplete social data
Models using real-time social data
Representations of social and behavioral theories in computational models
Simulation methodologies for social processes including numerical and
statistical methods
Models for network dynamism
Modeling human and social elements in cyber systems (e.g. cyber-physical
systems, socio-technical systems, and network centric systems)
Social Computing Algorithms for Parallel and Distributed Platforms
*Analysis of massive social data*
Algorithms for dynamic social data
Algorithms for social network analysis
Analysis methods for incomplete, uncertain social data
Social analysis methods on parallel and distributed frameworks
Social computing for emerging architectures (e.g. cloud,
multi-core/many-core, GPU, and mobile computing architectures)
*Application*
Emergency management (e.g. infrastructure resilience, natural disaster
management)
National security (e.g. political stability, counter-terrorism, and
homeland security)
Health science (e.g. disease spread models, health informatics, and health
care analytics)
Social media analytics (e.g. business analytics, political analysis, and
economic analysis)
PAPER SUBMISSION
Submitted manuscripts may not exceed ten (10) single-spaced double-column
pages using 10-point size font on 8.5x11 inch pages (IEEE conference
style), including figures, tables, and references.
Please visit the workshop website(http://www.lcid.cs.iit.edu/parsocial) for
details on submission.
*Workshop Organization*
**Workshop Co-Chairs**
Eunice E. Santos, Ron Hochsprung Endowed Chair and Professor of
Computer Science, Illinois Institute of Technology, USA
John Korah, Research Assistant Professor, Illinois Institute of
Technology, USA
**Steering Committee**
George Cybenko, Dorothy and Walter Gramm Professor of Engineering,
Dartmouth College, USA
Eugene Santos Jr., Professor of Engineering, Dartmouth College, USA
V. S. Subrahmanian, Professor of Computer Science, University of
Maryland, USA
James A. Hendler, Tetherless World Professor of Computer Science,
Rensselaer Polytechnic Institute, USA
------------------------------
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