SIGN Signum function. For each element of X, SIGN(X) returns 1 if the element is greater than zero, 0 if it equals zero and -1 if it is less than zero.For the nonzero elements of complex X, SIGN(X) = X ./ ABS(X).
Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data. Although Cytoscape was originally designed for biological research, now it is a general platform for complex network analysis and visualization. Cytoscape core distribution provides a basic set of features for data integration and visualization. Additional features are available as plugins . Plugins are available for network and molecular profiling analyses, new layouts, additional file format support, scripting, and connection with databases. Plugins may be developed by anyone using the Cytoscape open API based on Java™ technology and plugin community development is encouraged. Most of the plugins are freely available . 信息来自：http://www.cytoscape.org/
ISCNS 2011 nApril 23-24 Nanjing · Home · Organizing Committee · Invited Speakers · Program Schedule · Registration · Location and Sightseeing · Sponsors · Contact The 2011 International Symposium on Complex Networks and Systems (ISCNS'11) will be held on April 23-24 2011 in Nanjing, China, officially organized by the Department of Mathematics , Southeast University , China. The ISCNS'11 focuses on complex systems and networks, multi-agent systems, nonlinear dynamics and control, systems biology, sensor networks, communication networks, networked control systems, and their applications. The symposium will be sponsored by the Department of Mathematics , Southeast University , China. Latest News Due the limit budget, we cannot afford your travel fees in this workshop. What we can afford are the following: 1. your living cost (including 2 buffet lunch 自助餐 +1 banquet) 2. your accommodation fees in the reserved hotel 3. tour fee in Zhongshan Ling （中山陵） on 25 April after the workshop Please send me the filled accommodation form with some detailed information by 11 April so that we can reserve the accommodation for you. Program Schedule 23-24 April, 2011: Two-day Workshop Registration Apr. 22, 2011 （ Friday ） 9:00-21:00 Registration : Nanjing Shijiyuan Hotel (jinxianghe road 20) 南京世纪缘大酒店 ( 进香河路 20 号 ) 东南大学四牌楼校区 西门向南大约 800 米 Apr. 23, 2011 （ Saturday ） 9:00-17:40 Registration : Chunhui Hall ( 东南大学四牌楼校区春晖堂 ) 南京市四牌楼 2 号东南大学 Apr. 23, 2011(Saturday) Chunhui Hall(春晖堂) 09:00-09:30 OpenCeremony Session1 Chair:JindeCao 09:30- 10:20 Guanrong Chen LaplacianSpectra ofComplexNetworks andTheirEffects onSynchronization Performances 10:20- 10:40 TeaBreak 10:40- 11:30 Yusheng Xue TBD 12:00- 14:00 Lunch Session2 Chair:JinqingFang 14:00-14:50 Xiaofan Wang SocialLearningin ComplexNetworks 14:50-15:40 Binghong Wang TransportationDynamics onMobileNodeNetwork 15:40-16:00 TeaBreak 16:00-16:50 Jinqing Fang AFrameworkof Non-Equilibriumand EquilibriumStatistical EnsembleFormalism forComplexQuantumSystems 16:50-17:40 Fuchun Sun UniversalApproximationand ControlofMulti-Time-Scale DynamicalSystems 18:00 Banquet Apr.24,2011(Sunday) ChunhuiHall( 春晖堂 ) Session3 Chair:YuanqingXia 09:00-09:50 Jun-an Lu Synchronization-based ScalabilityofRingsand ChainsofDenseLumps 09:50-10:10 TeaBreak 10:10-11:00 Zhihong Guan ImpulsiveAlgorithms forConsensusof Multi-agentSystems 11:00-11:50 Yuanqing Xia AnalysisandSynthesisof NetworkedControlSystems 12:00- 14:00 Lunch Session4 Chair:WenwuYu 14:00-14:50 Zhisheng Duan Synchronizationof ComplexNetworksand ConsensusofMulti-AgentSystems: AUnifiedViewpoint 14:50-15:40 Daniel Ho APinningSchemeand AggregationApproach toComplexNetworks 15:40-16:00 TeaBreak 16:00-16:50 Guangming Xie ControlTheory forSmartSwarms 16:50-17:40 Wei Ren DistributedControl ofNetworkedMulti-agent Systems:Algorithms andApplications 17:40-18:00 ConclusionRemarks Apr. 25, 2011(Monday) Tourism in Zhongshan Ling（中山陵） All Rights Reserved 2011 - By ISCNS'2011
The 5-th Week Schedule Program Schedule "Recent Progresses in Complex Networks Research" The Fifth Week (Mar 28-April 1) ====================================== Mar 28 Monday 10:00-11:30 Chairperson ： Bing-Hong Wang B. Kahng （ Seoul National University ） : Explosive percolation transition of complex networks Lunch Break 15 ： 00-16:00 Chairperson ： Tao Zhou Wei Li (Max-Planck-Institute for Mathematics in the Sciences): Statistical Learning in an evolutionary game Mar 29 Tue 10:00-11:30 Chairperson ： Bing-Hong Wang Hawoong Jeong (Korea Advanced Institute of Science and Technology) ： S tructure and dynamics of the directed complex networks Mar 30 Wed 10:00-11:30 Chairperson ： Bing-Hong Wang Zhou, Changsong （ Hong Kong Baptist University ） ： Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations Mar 31 Thursday 10:00-11:30 Chairperson ： Bing-Hong Wang David Saad （ The Non-linearity and ComplexityResearch Group, Aston University ， UK ） Dynamics of Boolean networks - a Generating Functional Analysis Lunch Break 15 ： 00-16:00 Chairperson ： Tao Zhou You-Gui Wang ( Beijing Normal University): Self-Organized Criticality in Market Economies April 1 Friday 10:00-11:30 Chairperson ： Bing-Hong Wang Tao Zhou (University of Electronic Science and Technology of China) : 1, Link prediction in complex networks; 2, Information extracting from networks: ranking and recommending; Lunch Break 15:00-17:00 Chairperson ： Tao Zhou Discussion about recent progresses and future directions in complex networks research : All the participants: Chin-Kun Hu ， B.Kahng ， Beom Jun Kim, Bin Jiang ， Renaud Lambiotte ， Jing Zhao ， Hyunggyu Park, Hawoong Jeong, Sumiyoshi Abe, Jae Dong Noh, David Saad ， Changsong Zhou, Chenping Zhu, Wei Li, Zi-Ke Zhang, Lin-Yuan Lv ， Mingsheng Shang, Tao Zhou ， Bing-Hong Wang
The Fourth Week Schedule Interdisciplinary Applications of Statistical Physics Complex Networks (KITPC/ITP-CAS, Feb 28 - Apr 1, 2011) Week 4, Mar 21 – Mar 25, 2011 Monday 21 / 3 /201 1 Room: 6620 Chairperson: Bing-Hong Wang 10:00-11:00 Chin-Kun Hu （ Institute of Physics, Academia Sinica ， Taipei ） Some recent results for complex networks of nonlinear and biological systems' 11:00-11:30 Discussion Lunch Break Room: 6620 Chairperson: Tao Zhou 15:00-16:00 Bin Jiang (University of G?vle, Dept of Technology and Built Environment, Sweden) Scaling of geographic space with data-intensive geospatial computing. 16:00-16:20 Break 16:20-17:00 Jing Zhao (Department of Mathematics, Logistical Engineering University) Network based TCM pharmacology Tuesday 22 / 3 /201 1 Room: 6620 Chairperson: Bing-Hong Wang 10:00-11:00 Sumiyoshi Abe (Department of Physical Engineering, Mie University ) Aftershocks 11:00-11:30 Discussion Lunch Break Room: 6620 Chairperson: Tao Zhou 15:00-15:50 Renaud Lambiotte (Imperial College London; Institute for Mathematical Sciences ) Beyond Space For Spatial Networks 15:50-16:10 Break 16:10-17:00 Wen-Xu Wang (Arisona University, USA) TBA Wednesday 23 / 3 /201 1 Room: 6620 Chairperson: Bing-Hong Wang 10:00-11:00 Hyunggyu Park (School of Physics, Korea Institute for Advanced Study, Korea) Phase transitions on networks: Annealed verses quenched 11:00-11:30 Discussion Lunch Break Room: 6620 Chairperson: Tao Zhou 15:00-16:00 Renaud Lambiotte (Imperial College London; Institute for Mathematical Sciences) Multi-scale Modularity in Complex Networks 16:00-16:20 Break 16:20-17:00 Yueheng Lan (Department of Physics, Tsinghua University) Novel computation of the growth rate of generalized random Fibonacci sequences Thursday 24 / 3 /201 1 Room: 6620 Chairperson: Bing-Hong Wang 10:00-11:00 Beom Jun Kim (Department of Physics, Sungkyunkwan University, Korea) Synchronization in two coupled networks 11:00-11:30 Discussion Lunch Break Room: 6620 Chairperson: Tao Zhou 15:00-16:00 Renaud Lambiotte (Imperial College London; Institute for Mathematical Sciences) Multirelational Organization of Large-scale Social Networks in an Online World 16:00-16:30 Lin-Yun Lv ( ) TBA Friday 25 / 3 /201 1 Room: 6620 Chairperson: Bing-Hong Wang 10:00-11:00 Jae Don Noh (Department of Physics, University of Seoul, Korea ) Scaling behavior of random walk centrality in general graphs 11:00-11:30 Discussion Lunch Break Room: 6620 Chairperson: Tao Zhou 15:00-16:00
应Lambert Academic Publishing之邀，我写的书 Modularity: The Principle of Evolution in Complex Systems今天出版了。 此书总结了我数年来在复杂网络，金融物理，和免疫系统进化方面的工作。主题围绕着“模块化” (modularity)展开。此书的核心是提出了生物进化中的模块化定律。 Modularity, understanding systems as the combination of separated components, is a prevalent concept in biology, social science and engineering design. This book offers a general theoretical model of emergence of modularity during evolution in changing environments. Evidences from protein interaction network and protein domain network support this theory as a general law of evolution in complex systems. Applying it to animal development, this theory appears to provide an explanation for the occurrence and timing of the Cambrian explosion. Applying it to trade networks, this theory predicts that globalized economy is more sensitive to recessions. This book also introduces a quantitative measure of hierarchy, a statistical method to predict the dominant flu strain and the first theoretical model to explain the bacterial acquired immunity (CRISPR). The information in the book should help shed some light in the study of complex systems, flu vaccine, and bacterial antibiotic resistance. 购买链接: http://www.amazon.com/Modularity-principle-evolution-complex-systems/dp/3844311416 前后封面
The 2011 International Symposium on Complex Networks and Systems (ISCNS'11) http://www.ee.cityu.edu.hk/~wwyu/ISCNS11/index.html Welcome The 2011 International Symposium on Complex Networks and Systems (ISCNS'11) will be held on April 23-24 2011 in Nanjing, China, officially organized by the Department of Mathematics , Southeast University , China. The ISCNS'11 focuses on complex systems and networks, multi-agent systems, nonlinear dynamics and control, systems biology, sensor networks, communication networks, networked control systems, and their applications. The symposium will be sponsored by the Department of Mathematics , Southeast University , China. Latest News We will cover the travel (hard-seat tickets if by trains) and accommodation fees (in the reserved hotel) for some students and young teachers. Note that there are limited quota. Please send your registration form to us as soon as possible. All Rights Reserved 2011 - By ISCNS'2011 General Chairs Jinde Cao (SEU, China) Jijun Liu (SEU, China) Organizing Committees Jinling Liang (SEU, China) Qingshan Liu (SEU, China) Jianquan Lu (SEU, China) Xingmei Xue (SEU, China) Wenwu Yu (SEU, China) Invited Speakers (listed not in any particular order) Confirmed Guanrong Chen (CityU, HK) Zhisheng Duan (Peking University, China) Jinhu Lv (Chinese Academy of Sciences, China) Daniel W. C. Ho (CityU, HK) Yuanqing Xia (Beijing Institute of Technology, China) Unconfirmed Program Schedule 23-24 April, 2011: Two-day Workshop Related Download under construction Send Registration Form To Wenwu Yu Email: wenwuyu@gmail.com ; wwyu@seu.edu.cn Telephone: 0086-15051861330 Registration Form Download Sponsors Department of Mathematics , Southeast University , China Contact Dr. Wenwu Yu Department of Mathematics , Southeast University Nanjing 210096, P. R. China Tel: +86-25-52090596-8531 Fax: +86-25-83792316 Email: wenwuyu@gmail.com ; wwyu@seu.edu.cn
110221-Complex_systems_A_survey.pdf Complex Systems: A Survey M. E. J. Newman Department of Physics, University of Michigan, Ann Arbor, MI 48109 and Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI 48109 A complex system is a system composed of many interacting parts, often called agents, which displays collective behavior that does not follow trivially from the behaviors of the individual parts. Examples include condensed matter systems, ecosystems, stock markets and economies, biological evolution, and indeed the whole of human society. Substantial progress has been made in the quantitative understanding of complex systems, particularly since the 1980s, using a combination of basic theory, much of it derived from physics, and computer simulation. The subject is a broad one, drawing on techniques and ideas from a wide range of areas. Here I give a short survey and an annotated bibliography of resources for those interested in learning about complex systems. I. INTRODUCTION Complex systems is a relatively new and broadly interdisciplinary field that deals with systems composed of many interacting units, often called “agents.” The foundational elements of the field predate the current surge of interest in it, which started in the 1980s, but substantial recent advances in the area coupled with increasing interest both in academia and industry have created new momentum for the study and teaching of the science of complex systems. There is no precise technical definition of a “complex system,” but most researchers in the field would probably agree that it is a system composed of many interacting parts, such that the collective behavior of those parts together is more than the sum of their individual behaviors. The collective behaviors are sometimes also called “emergent” behaviors, and a complex system can thus be said to be a system of interacting parts that displays emergent behavior. Classic examples of complex systems include condensed matter systems, ecosystems, the economy and financial markets, the brain, the immune system, granular materials, road traffic, insect colonies, flocking or schooling behavior in birds or fish, the Internet, and even entire human societies. Unfortunately, complex systems are, as their name makes clear, complex, which makes them difficult to treat scientifically. Experimental observations are of course possible, though these fall largely within the realm of the traditional scientific disciplines and are usually not considered a part of the field of complex systems itself, which is primarily devoted to theoretical developments. Complex systems theory is divided between two contrasting approaches. The first involves the creation and study of simplified mathematical models that do not claim to mimic quantitatively the behavior of real systems but instead try to abstract their most important qualitative elements into a solvable framework from which we can gain scientific insight. The tools used in such studies include dynamical systems theory, information theory, cellular automata, networks, computational complexity theory, and numerical methods. The second approach is to create systematic computer simulations of the interacting parts of a complex system, often down to minute details, and then watch and measure the emergent behaviors that appear. The primary tool for this approach is agent-based simulation, around which a community of computer scientist scientists and software developers has grown up to create software tools for sophisticated computational research in complex systems. This resource letter focuses on the methods and theoretical tools of complex systems, including both the modeling and simulation approaches above, though I also include a short section of references to individual specific complex systems, such as economies or ecosystems, which can serve as a concrete foundation motivating the theoretical studies.
Copyright by SIAM. Unauthorized reproduction of this article is prohibited. SIAM R EVIEW _ c 2010 Society for Industrial and Applied Mathematics Vol. 52, No. 2, pp. 294314 Complex Singularities and the Lorenz Attractor Divakar Viswanath Sonmez Sahuto?glu Abstract. The Lorenz attractor is one of the best-known examples of applied mathematics. However, much of what is known about it is a result of numerical calculations and not of mathematical analysis. As a step toward mathematical analysis, we allow the time variable in the three-dimensional Lorenz system to be complex, hoping that solutions that have resisted analysis on the real line will give up their secrets in the complex plane. Knowledge of singularities being fundamental to any investigation in the complex plane, we build upon earlier work and give a complete and consistent formal development of complex singularities of the Lorenz system using the psi series . The psi series contain two undetermined constants. In addition, the location of the singularity is undetermined as a consequence of the autonomous nature of the Lorenz system. We prove that the psi series converge, using a technique that is simpler and more powerful than that of Hille, thus implying a two-parameter family of singular solutions of the Lorenz system. We pose three questions, answers to which may bring us closer to understanding the connection of complex singularities to Lorenz dynamics. Key words. Lorenz attractor, psi series, complex singularities AMS subject classifications. 34M 35, 37D45 DOI. 10.1137/090753474 Complex Singularities and the Lorenz Attractor
Some Recent Advances in Complex Networks Synchronization _ Guanrong Chen, Xiaofan Wang, Xiang Li, and Jinhu Lv (陈关荣,汪小帆,李翔,吕金虎) 按语: 我把陈关荣等四位合作的文章推荐到这个专栏,完全是为了推动博文比赛. 因为 他们当中有三位是评委,自然将不参加评选. （方锦清2010、3、27） Abstract. The current study of complex dynamical networks is pervading almost all kinds of science, engineering and technology, ranging from mathematics to computers, physics to biology, even to sociology. Its impacts on the modern high-tech industries, financial markets and human life are prominent and will be far-reaching. Research on fundamental properties and dynamical features of such complex networks has indeed become overwhelming. This Chapter presents a brief overview of some past and current studies on the subject of complex dynamical network synchronization, particularly from an engineering and technological perspective. Some commonly concerned issues in the current research of network synchronization, mainly on Some recent advances in complex network synchroniz
Chaos 16, 015104 (2006) Changsong Zhou and Jurgen Kurths 这是一篇我看到的极出色的文章，所研究的复杂网络上的分层同步（我就直译了）问题对识别网络的拓扑结构具有启发性。PRE80，016116（2009）也正是基于此，明确提出了用来网络探测。在没有看到更早的文献之前，我先当它是利用动力学来探测网络度分布的第一文了。如此说，EPL82，68001（2008）可能要觉得有点冤，因为那里宣称是首次。但在仔细阅读这三文章之后，我还是认为这里闪烁的原创性更明亮！ 文章的摘要：We study synchronization behavior in networks of coupled chaotic oscillators with heterogeneous connection degrees. Our focus is on regimes away from the complete synchronization state, when the coupling is not strong enough, when the oscillators are under the influence of noise or when the oscillators are nonidentical. We have found a hierarchical organization of the synchronization behavior with respect to the collective dynamics of the network. Oscillators with more connections (hubs) are synchronized more closely by the collective dynamics and constitute the dynamical core of the network. The numerical observation of this hierarchical synchronization is supported with an analysis based on a mean field approximation and the master stability function. 1.在简介里隐约给出了复杂网络的研究对象主要就是指联接，或称为复杂的拓扑结构。而对于结点的研究则是动力学的范围。所以是否可以将我们研究的对象分为这么两层次：复杂系统是第一层、复杂网络与动力系统（微分动力系统）是第二层，这一层是拓扑结构与单一结点动力学。在第二层次上的单独研究都已经开展得很多了，而第一层的研究则包括常见的什么传播动力学、网络同步等。 2.MSF分析的是网络的完全同步（CS），但是网络的最自然状态往往是非完全同步的。在这种情况下，局部群体行为的分析也是十分令人感兴趣的。这对应以往斑图研究中的发达湍流与全局同步运动（规则斑图之一）之间的状态。当然以前斑图研究的也可以说成是简单连接的网络上的动力学研究。 3.Interestingly, the stability analysis of the CS state can be adopted to provide an understanding of the hierarchical synchronization.这是在简介结尾时说的一句话，可能是对应II（E）部分的，平均场分析。因为这一部分的分析方法与MSF相似。不同的是normalized耦合强度是结点度的显函数，且由之可知度大的结点耦合强度也大。所以可想而知的是有权连接对所讨论的对象也有很大的影响。 4.文章最后一句Our present interest is on self-organization of structures and dynamics due to the interplay between them令人浮想连翩。 5.总体还有个感觉就是工作量很大，做得很细，值得学习。
Fig. 1 The more connection and species, the more unstable Recently my former group published one paper about the stability of complex food network in the journal 'Science'. This is not my direction. But I am near enough to understand their ideas of research. The basic question came from Robert May in the 70s. He found that there is a dilemma between the theory and the observation. People generally believe that the diversity in an ecological system makes it stable. But May showed it mathematically that with increasing connection links and interactive nodes, an ecological system will become more and more unstable. People with the experience of solving large nonlinear differential equations know that the system becomes more and more difficult to have steady states if the number of equations increase. So Which is correct: our intuition or our model? In this papery, they used a small trick before the simulation. If there is a steady state in a dynamic system, you can always re-scale the time for different variables to normalize one steady state to an unit vector = (1, 1, ..., 1). Then you can do usual stability analysis around this point. Based on Monte Carlo sampling of different parameters, you will know how they effect the stability of the system around this steady state locally. Using this half-analytical-half-numeric method, they generated 100 million food webs randomly and made a statistic how different factors effect the stability. They found that more connections and more species really de-stabilize the ecological system. That is, in a forest, if trees, birds, insects etc. form more connections and there are more species, the ecological system in this forest will be more inclined to collapse! (Really unintuitive?) The other conclusion is that the food web will be more stable if top predators like lions, tigers die fast, or they can eat more deer when deer population increases. This kind of idea is actually not new. In 1960s, when Kauffman tried to study the gene regulatory network of the living organism, he did the same thing by creating millions of random networks since the real genetic networks would come decades later (He simply can not wait). Based on his statistics on all these random gene networks, Kauffman concluded that if we need an evolution in Life, we have to have our gene network at the edge of Chaos. That is, it is not either in deterministic system with the fixed number of steady states, nor in totally chaos without any steady states at all. It is just at this delicate zone in between. Could this complexity analysis with large number of simulations will reveal more 'emergent properties' in Life? Let's just wait and see. Ref: Thilo Gross, Lars Rudolf, Simon A. Levin, Ulf Dieckmann, Generalized Models Reveal Stabilizing Factors in Food Webs, Science 7 August 2009, Vol. 325. no. 5941, pp. 747 - 750,DOI: 10.1126/science.1173536 END
Complex09 Call For Participation Welcome to Complex2009 The First International Conference on Complex Sciences: Theory and Applications 发件人Xiao Shi XiaoShi@ntu.edu.sg 回复Xiao Shi XiaoShi@ntu.edu.sg 发送至 COMPLEX_2009@mlist.ntu.edu.sg 日期2009年2月17日 下午7:03 主题Complex09 Call For Participation 邮送域mlist.ntu.edu.sg 隐藏详细信息 2月17日 (3天前) 回复 The interdisciplinary studies on complex systems have gained extensive research interests. Significant impacts have been made by such studies on a wide range of different areas including physics, biology, economics, social sciences, etc., and penetrating into various engineering applications. In the long-term future, the way we understand and cope with the world may all be revolutionized by such studies. Complex'2009, the First International Conference on Complex Sciences: Theory and Applications, aims to provide a unique and convenient platform for people working on theory and applications of complex systems to exchange their ideas and their latest research results. Topics of interests address, but not limited to, the following areas: - Structure and Dynamics of Complex Networks - Complex Biological Systems - Econophysics - Sociophysics - Complex Systems Methods - Complex Systems in Engineering We look forward to your participation in COMPLEX'2009 to make this conference a success. CONFERENCE DATE AND LOCATION February 23-25, 2009, Shanghai, China CONFERENCE PROGRAM The detailed conference program is available at http://www.complex-sys.org/ . The conference features: - Seventeen technical sessions consisting of more than 190 high-quality technical papers - Five collated workshops. - Four Distinguished Keynote Speakers and Fifteen Invited Speakers. COLLATED WORKSHOPS Causality in Complex Systems (ComplexCCS) http://www.complexsystems.net.au/wiki/Complex_%2709_Workshop_on_Causalit y_in_Complex_Systems Complex Engineering Networks (ComplexEN) http://complexen.icstweb.org/ Complexity Theory of Arts and Music (COART) http://coart.icstweb.org/ Modelling and Analysis of Human Dynamics (MANDYN) http://pil.phys.uniroma1.it/~gcalda/Complex2009Satellite/ Social Physics and its Applications (SPA) http://socialphysics.ac.cn/NewsView.Asp?id=46 For further information and registration: http://www.complex-sys.org/ 回复 全部回复 转发
The Complexity Science Group in the Department of Physics Astronomy at the University of Calgary invites applications for a PhD position in the field of complex network theory with applications to neurosciences. The successful applicant is expected to work closely with other members of the Complexity Science Group and members of the Hotchkiss Brain Institute in an interdisciplinary environment. A background in statistical physics, computational physics, time series analysis, complex network theory and/or information theory is beneficial. Applicants should send an email to davidsen(at)phas.ucalgary.ca that includes a CV with a list of publications and a brief statement of research interests. Review of applications will begin on January 30, 2009 and continue until the position is filled. More information about the group is available at www.ucalgary.ca/complexity More detalis about the job in PDF fie: PhD Complex in neuroscience
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