CFP: Mathematics in Computer Science, Special Issue on Mathematics, Data and Knowledge

There is a growing interest in applying mathematical theories and methods (from topology, computational geometry, differential equations, fluid dynamics, quantum statistics, etc.) to describe and to analyze scientific regularities of diverse, massive, complex, nonlinear, and fast changing data accumulated continuously around the world and in discovering and revealing the valid, insightful, and valuable knowledge that data imply. With increasingly solid mathematical foundations, various methods and techniques have been studied and developed for data mining, modeling, and processing, and knowledge representation, organization, and verification; different systems and mechanisms have been designed to perform data-intensive tasks in many application fields for classification, predication, recommendation, ranking, filtering, etc. This special issue of Mathematics in Computer Science invites submissions of original research articles on the exploration of new mathematical theories and methodologies for data modeling and analysis, and knowledge discovery and management, on the study of existing mathematical models of big data and complex knowledge, and on the development of novel solutions and strategies to enhance the performance of existing systems and mechanisms for data and knowledge processing.

Specific topics include, but are not limited to:
• Mathematical foundations and theories for data-intensive and knowledge-based systems
• Mathematical, statistical, and dynamic analysis of data and knowledge models
• Mathematical methods for big data storage, transferring, and processing
• Mathematical methods for complex knowledge representation, organization, visualization, and management
• Mathematical methods for data mining, pattern recognition, artificial intelligence, and knowledge discovery
• Algebraic, geometric, analytic, discrete, probabilistic, fuzzy, rough set, and cognitive modeling of recommendation systems, ranking systems, rating systems, expert systems, etc.
• Mathematical theories for the development of evolutionary computing, neural networks, and genetic algorithms
Important Dates
• Deadline for paper submission: March 31, 2013
• Notification of acceptance: August 15, 2013
• Final paper submission: October 1, 2013
• Publication of special issue: December 2013

Submission Guidelines

Authors are encouraged to prepare submissions by using LaTeX with the class file mathincl.cls. Papers should be sent as PDF files to special.issue.mdk@gmail.com. All submitted papers will be refereed according to the usual MCS refereeing process. More information can be found at: http://mine.kaust.edu.sa/Pages/CFP-MCS-SI.aspx.

Guest Editors

Xiaoyu Chen, School of Computer Science and Engineering, Beihang University, China
Dongming Wang, Laboratoire d’Informatique de Paris 6, CNRS-UPMC, France
Xiangliang Zhang, King Abdullah University of Science and Technology, Saudi Arabia

Full Professor in Advanced Analytics

School of Business and Economics

We are seeking qualified applicants for teaching and research in the area of Advanced Analytics. The starting date is as soon as possible.

Within the “Excellence Initiative” – the German federal and state governments’ framework to promote cutting-edge research in and to enhance the quality of the country’s universities – the School of Business and Economics at RWTH Aachen University is currently in the process of establishing four Research Areas. All four of them will be brought together under one roof, that of the Interdisciplinary Management Factory (IMF), which will serve to substantially enhance the School’s research profile. Each Research Area will address global challenges, which can only be tackled via interdisciplinary and integrated research – a form of research that one of Europe’s leading universities of technology is optimally equipped to carry out.

The successful candidate will play a crucial role in establishing the Research Laboratory of the Operations Research and Management Research Area (ORM). The actors in this Research Area are economists, mathematicians, and computer scientists, whose research interests embrace operations research, operations management, discrete optimization, and efficient algorithms. The successful candidate will be expected to contribute to this pool of expertise with know-how from fields like prescriptive analytics, big data, or optimization under uncertainty/robust optimization. Apart from having conducted top-level research, reflected in publications in high-ranking journals, applicants should also demonstrate a successful professional orientation. Experience in procuring third-party funding is also very desirable. The teaching load will encompass two hours per semester. The professorship is limited to a period of four years.

A Ph.D. degree is required; additionally, Habilitation (post-doctoral lecturing qualification), an exemplary record of research achievement as an assistant / an associate / a junior professor or university researcher and/or an outstanding career outside academia are highly desirable. Ability in and commitment to teaching are essential. German is not necessary to begin. Applications from early-stage researchers are particularly welcome. Should more detailed information about this position be required, please contact Prof. Marco Lübbecke (luebbecke@or.rwth-aachen.de), who heads the ORM Research Area.

The application should include supporting documents regarding success in teaching.

Please send a cover letter stating research aims and a CV to: An den Dekan der Fakultät für Wirtschaftswissenschaften der RWTH Aachen, Prof. Dr. Oliver Lorz, D-52056 Aachen, Germany. The deadline for applications is December 12, 2012.

This position is also available as part-time employment per request.
RWTH Aachen University is certified as a family-friendly university and offers a dual career program for partner hiring. We particularly welcome and encourage applications from women, disabled people and ethnic minority groups, recognizing they are underrepresented across RWTH Aachen University. The principles of fair and open competition apply and appointments will be made on merit.

Postdoc: probabilistic ML and intensive care unit data

We are seeking a postdoctoral researcher at the University of Edinburgh to work on a project to develop and validate advanced statistical methods for analyzing time-series data from adult neuro-intensive care unit (NICU) patients.

The project would be suitable for candidates with a strong background in probabilistic machine learning who are keen to work on a challenging application area.

The researcher will be a part of the School of Informatics at the University of Edinburgh. This is an opportunity to work in a world-leading machine learning group, including seven faculty in the area. More broadly, a recent international review described the School as an “elite” department of computer science in Europe, and in national research assessment exercises, the School of Informatics has consistently ranked at the top in the UK for research quality.

In the first year the Research Associate will focus on methods for inferring physiological and artifactual events from time-series data, including data cleansing, anomaly detection, and inference in probabilistic models. This work will build on that of Quinn, Williams and McIntosh (PAMI, 2009) on Factorial Switching Linear Dynamical Systems applied to Physiological Condition Monitoring. In the second year of the project the models will be validated against live data collected at the NICU in the Southern General Hospital (Glasgow), and development of the models continued in light of the results obtained.

The postdoctoral researcher will be supervised by Prof Chris Williams , who may be contacted for informal enquiries.

For more information about the project and information about how to apply, please see http://homepages.inf.ed.ac.uk/ckiw/mypages/postdoc2013.html

or
https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=007123

Please note the closing date of THURSDAY 10 JANUARY 2013, at 5pm UK time.

Chris Williams ckiw@inf.ed.ac.uk
Institute for Adaptive and Neural Computation School of Informatics, University of Edinburgh
10 Crichton Street, Edinburgh EH8 9AB, UK
tel: +44 131 651 1212 fax: +44 131 650 6899 http://homepages.inf.ed.ac.uk/ckiw/

Call for Papers CAIP 2013

CALL FOR PAPERS

CAIP 2013

15th International Conference on
Computer Analysis of Images and Patterns

27-29 August 2013

York, United Kingdom

http://http://www.cs.york.ac.uk/cvpr/caip2013/

CAIP 2013 is the fiftheenth in the CAIP series of biennial
international conferences devoted to all aspects of Computer
Vision, Image Analysis and Processing, Pattern recognition
and related fields. CAIP2013 will be hosted by York University
and held in August 27-29, in York, UK. The scientific program
of the conference is presented in a single track and the
proceedings of the conference will be published by the
Springer LNCS series.

The scope of CAIP’13 includes, but not limited to, the following
research areas:

– 3D Vision
– 3D TV
– Biometrics
– Color and texture
– Document analysis
– Graph-based Methods
– Image and video indexing and database retrieval
– Image and video processing
– Image-based modeling
– Kernel methods
– Medical imaging
– Mobile multimedia
– Model-based vision approaches
– Motion Analysis
– Natural computation for digital imagery
– Non-photorealistic animation and modeling
– Object recognition
– Performance evaluation
– Segmentation and grouping
– Shape representation and analysis
– Structural pattern recognition
– Tracking
– Applications

Important Dates:

Paper Submission: 1 April 2013
Author Notification: 15 May 2013
Camera-ready paper due: 1 June 2013
CAIP 2013 Conference: 27-29 August 2013

General chair:

Edwin Hancock

Organization Committee:

Adrian G. Bors
Will Smith
Richard Wilson

Workshop ‘Industry & Practices for Forecasting’ in the greater Paris area

This is a call for contributions for the following 3-day workshop:
*Industry & Practices for Forecasting — second edition* to be held 3 miles away from Paris, from June 5 to 7, 2013.

Its focus is on the forecasting of time series using stochastic modeling and/or learning methods, in a high dimensional context.

The purpose is to bring together academics and industry professionals to share different experiences and discuss future trends related to this area.
Both theoretical and practical issues will be considered.
The industries at hand are: energy, finance, transportation, networks, IT, meteorology, health research and environment.

This workshop will consist of plenary sessions (about 1 hour) and contributed sessions (about 30 min).

Plenary talks will be given by:
– Gabor LUGOSI, Pompeu Fabra University, Spain
– Shie MANNOR, Technion University, Israel
– Axel MUNK, Georg-August-University of Gottingen, Germany
– Peter BUHLMANN, ETH Zurich, Switzerland
– Eric KOLACZYCK, Boston University, USA
– Pierre PINSON, DTU, Denmark

For the regular sessions, the program committee chaired by Anestis ANTONIADIS (Université J. Fourier, Grenoble, France) invites the submission of abstracts related the aforementioned topics.

A selection of papers will be invited for inclusion in a proceedings volume (most likely, in some Springer series).

Now that you have most of the information, see http://conferences-osiris.org/sites/default/files/osiris/wipfor/wipfor13/CallForPapers-2013-11-26.pdf
for a more detailed call for submissions.

Gilles Stoltz, on behalf of the program committee of WIPFOR’2013

4 PhD positions and 1 post-doc position in Statistical Machine Translation at the Informatics Institute, University of Amsterdam, The Netherlands.

—
Apologies for cross-posting.
It would be appreciated if you could forward this to any interested parties.
—

Applications are invited for four fully-funded 4-year PhD positions and one fully-funded 3-year post-doc position in the area of Statistical Machine Translation. The positions are funded through an advanced research fellowship (Vidi scheme) by the Dutch Science Foundation (NWO) and a governmental research grant.

Please find further details (including the application procedure) for the PhD positions at:
http://www.uva.nl/over-de-uva/werken-bij-de-uva/vacatures/item/12-289.html

and further details about the post-doc position at:
http://www.uva.nl/over-de-uva/werken-bij-de-uva/vacatures/item/12-288.html

The application deadline for all positions is 15 December, 2012.
The starting date for all positions is early 2013.

Research Description

The research positions focus on improving state-of-the-art statistical machine translation approaches by investigating how better modeling of the generation process can be utilized to realize more fluent and accurate translations. The research will aim to substantially improve machine translation quality by achieving:

– robust translation quality across different genres, ranging from
formal language use in legal documents to casual language use in
social media;

– improved modeling of domain independent machine translation,
spanning legal, political, entertainment, and sports documents;

– improved modeling of fluency criteria, in particular for languages
for which only limited training data are available.

You will be supervised by Dr. Christof Monz and based in the Informatics Institute at the University of Amsterdam. The Informatics Institute consists of more than 40 members of permanent research faculty, over 25 post-doctoral researchers, and more than 100 PhD students, together representing more than a dozen nationalities.
Members of the institute are actively pursuing a variety of research initiatives, including machine translation, natural language processing, (cross-language) information retrieval, social network analysis, computer vision, machine learning, and multi-agent systems.

Requirements

You must have an MSc (for the PhD positions) or a PhD (or close to completion, for the post-doc position) in computer science, artificial intelligence, computational linguistics or a closely related area. In addition, you should

– (for the post-doc position only:) have a strong track record of
successful implementation and publication in natural language
processing or machine learning. A background in statistical machine
translation is a plus;

– have strong curiosity to solve problems in natural language processing;

– have a strong background in probability theory, statistics, and
machine learning;

– have excellent programming skills in at least two of the following
languages: C, C++, Java, Python, or Perl;

– enjoy working with real-world problems and real-word, large data
sets;

– have excellent communication skills, both oral and written;

– enjoy working in a closely collaborating team.

For specific questions you can get in touch with Christof Monz
email: c.monz@uva.nl

Postdoctoral position at the University of Paris-Sud/CNRS

The Machine Learning (AppStat) group of the Linear Accelerator Laboratory (LAL) is seeking a postdoctoral researcher for working on machine learning motivated by experimental physics. The position is financed by the ANR Siminole project (http://siminole.lal.in2p3.fr). Some of the ongoing themes are large scale MCMC in hierarchical parametric models, budgeted learning for real-time triggers, and unsupervised (deep) feature learning for next-generation high-resolution pixel calorimeters. All themes include the development of state-of-the-art ML solutions that can make a real difference in both the design and in the data analysis phases of ongoing and future large-scale physics experiments (e.g., Auger, LHCb@CERN, the future ILC or JEM EUSO). The ideal candidate should have a recently completed Ph.D. in the areas of machine learning or computational statistics, and an open spirit to work with researchers of different disciplines.

AppStat (http://appstat.lal.in2p3.fr) is an interdisciplinary research group with the mission of creating a scientific link between experimental physics and machine learning. AppStat is part of the Linear Accelerator Laboratory (LAL) and it also has strong ties to the Machine Learning and Optimization team (http://tao.lri.fr) of the Computer Science Laboratory (LRI). Both laboratories are part of the University of Paris-Sud campus, located in the outskirts of Paris. The position is available for a period of two years starting in February, 2013. The monthly salary is in the 2500-3000 euro range depending on experience. Interested candidates should send a cover letter, a curriculum vitae, and the names and addresses of three referees before December 20, 2012 to Dr. Balázs Kégl (balazs.kegl@gmail.com), and should be ready for an interview in the beginning of January.

PS: I will be at NIPS, don’t hesitate to contact me if you would like to discuss the position.

ESANN 2013: deadline extension

ESANN 2013

21st European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning
Bruges (Belgium) – April 24-25-26, 2013
http://www.esann.org/

Submission deadline extension
======================================================

Due to numerous requests, the deadline to submit papers to the ESANN 2013 conference has been extended to December 7, 2012. Please note that no further extension will be given.

Looking forward to seeing you at ESANN 2013,
The organizing committee.

========================================================
ESANN – European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning
http://www.esann.org/

* For submissions of papers, reviews, registrations:
Michel Verleysen
Univ. Cath. de Louvain – Machine Learning Group
3, pl. du Levant – B-1348 Louvain-la-Neuve – Belgium
tel: +32 10 47 25 51 – fax: + 32 10 47 25 98
mailto:esann@uclouvain.be

* Conference secretariat
d-side conference services
24 av. L. Mommaerts – B-1140 Evere – Belgium
tel: + 32 2 730 06 11 – fax: + 32 2 730 06 00
mailto:esann@uclouvain.be
========================================================

Positions at LSE

The LSE (London School of Economics) has advertised twenty new positions across all its departments (which include mathematics and statistics) and at all levels, from lecturer (=assistant professor) to professor (=full professor). See http://www.lseglobaldebate.com
The deadline is 7 December.

LSE, as a Social Sciences university, does not have a computer science department or departments in traditional sciences, but has active research groups in the areas of discrete mathematics and algorithms, game theory, financial mathematics, and many areas of statistics.

It’s an open recruitment exercise, in the sense that departments have not each been given fixed numbers of positions, but essentially will be in competition with each other for the positions. So it is a fairly unusual hiring exercise. When applying, candidates are asked to indicate which department they would want to belong to (and interdisciplinary will be likely to be viewed positively). If you might be interested in applying, with a view to joining the Mathematics department (and/or the Statistics department, with whom we work closely), and would like to discuss, please contact me (m.anthony@lse.ac.uk) and/or the head of the Mathematics department, Jan van den Heuvel (j.van-den-heuvel@lse.ac.uk).

Phd position in active perception and control at the University of Amsterdam

The Informatics Institute at the University of Amsterdam invites applications for a fully funded position for a PhD student in the area of active perception and control. The position is within the Intelligent Systems Lab Amsterdam and will be supervised by dr. Gwenn Englebienne and dr. Shimon Whiteson.

Application closing date: 15 December 2012, or until position is filled
Starting date: 1 February 2013
Duration: 4 years

The research will focus on the development of active perception and control algorithms for teams of robots. This will require advancing the state of the art in computer vision, multimodal perception, and decision-theoretic planning and learning. The research will be conducted as part of a European project called “Multi-Robot Cognitive Systems Operating in Hospitals (MOnarCH)” in which the University of Amsterdam collaborates with several other European universities and companies. The project aims to develop a network of heterogeneous robots and sensors for deployment in the pediatric area of an oncological hospital. It will handle uncertainties introduced by people and robots, generate natural interactions, and engage in edutainment activities.

Applicants must have a master’s degree in computer science or a closely related area. In addition, a successful candidate should have:

* strong math and programming skills.

* strong background in artificial intelligence: particularly useful is knowledge of machine learning, reinforcement learning, robotics, and computer vision. Experience with human-computer interaction and multimodal interfaces are a plus.

* strong oral and written communication skills.

The successful candidate will be based in the Intelligent Systems Lab Amsterdam (ISLA) within the Informatics Institute at the University of Amsterdam. The institute was recently ranked among the top 50 computer science departments in the world by the 2011 QS World University IT Rankings. ISLA consists of 20 members of faculty, 20 postdoctoral researchers, and more than 50 PhD students. Members of the lab are actively pursuing a variety of research initiatives, including machine learning, decision-theoretic planning and learning, multiagent systems, human-computer-interaction, natural language processing, information retrieval, and computer vision.

Some of the things we have to offer:

* competitive pay and excellent benefits
* extremely friendly working environment
* high-level of interaction
* location near the city center (10 minutes by bicycle) of one Europe’s most beautiful and lively cities
* international environment (10+ nationalities in the group)
* access to high-end computing facilities (cluster with 4,000+ cores)
* brand-new building

Since Amsterdam is a very international city where almost everybody speaks and understands English, candidates need not be afraid of the language barrier.

For further information, including instructions on submitting an application, see the official job ad at bit.ly/STd3O2.

Informal inquiries can be made by email to Gwenn Englebienne (g.englebienne@uva.nl) and Shimon Whiteson (s.a.whiteson@uva.nl).