1. NEW AFFILIATES. We welcome:

2. AJL. This is a reminder that NISS will operate the Affiliates Job Listings again this year. For those who are new to the Program and to remind everyone, the AJL is simply a centralized listing of job opportunities at the NISS Affiliates and NISS/SAMSI University Affiliates, and is located on the NISS Web site at

http://www.niss.org/affiliates/ajls.html

We publicize the AJL widely. Last year, there were more than 2 dozen listings, and more than a thousand hits to the page.

The AJL is open to all affiliates. Last year, there was a good mix of academic, government and industrial positions, and I hope for the same this year. Material for the AJL should be sent to Katherine Kantner (kak@niss.org). ASCII text is the preferred format (be sure that hyperlinks are clear), but we can handle almost anything.

3. UPCOMING AFFILIATES EVENTS

4. POSTDOCTORAL APPOINTMENTS. NISS has project needs and funds to make several postdoctoral appointments between now and next summer. Areas include digital government (data confidentiality, data integration and data quality), dynamics of social networks, education statistics, software engineering, statistical disclosure limitation for geospatial image data, and bioinformatics. Involvement with SAMSI programs is possible. Please make students and young colleagues aware of these wonderful opportunities. Information and a downloadable announcement are available on the NISS web site, at

http://www.niss.org/postdoc_info.html

In particular, there is a unique opportunity for a postdoctoral fellow to join the NSF-funded NISS project "Dynamics for Social Networks Processes: Comparing Statistical Models with Intelligent Agents."

The project abstract appears below. Principals are David L. Banks, Professor of the Practice of Statistics at Duke University, H. T. Banks, University Professor and Drexel Professor of Mathematics and Director, Center for Research in Scientific Computation, at North Carolina State University, Kenneth A. Bollen, Henry Rudolph Immerwahr Professor of Sociology and Director, Odum Institute for Research in Social Science, University of North Carolina at Chapel Hill, Kathleen Carley, Professor of Computation, Organizations, and Society in the Institute for Software Research International, School of Computer Science, and Director, Center for Computational Analysis of Social and Organizational Systems at Carnegie Mellon University, and Negash Medhin, Professor of Mathematics at North Carolina State University.

Criteria for selection include demonstrated research ability in statistics, applied mathematics or the relevant computational or social sciences, strength in computation and in verbal and written communication, and genuine commitment to cross-disciplinary research.

The position is available immediately, and the goal is for the appointment to begin not later than January 1, 2005. Unfortunately, funding is available for only nine months, although the appointment might be coupled with involvement in other NISS projects or activities at SAMSI. The salary is at the annual rate of $62,500. The appointment may be made at any time.

Applications should consist of a letter of interest containing addresses, telephone numbers and citizenship status; three letters of reference; a one-page biographical sketch; a publication record or dissertation abstract; and a one-page statement of interest in the project. These items are to be submitted by E-mail, as PDF files if possible, to postdoc-application@niss.org. Please sure to state interest in the "Social Networks Project."

Women and members of minority groups are particularly encouraged to apply. NISS is an AA/EEO employer.

PROJECT ABSTRACT

The goal of this project is to reconcile two methods for modeling change in social networks over time: a class of statistical models and intelligent agent models. The research contrasts the properties of these two approaches, exploring what qualitative dynamic behaviors in social networks are captured usefully and interpretably by each. The primary tools are latent variable representations and dynamical systems analysis. The result is a framework that characterizes the strengths and limitations of the two classes of models in multiple settings, and provides feedback that stimulates refinement of existing theories for social networks and development of new theory.

Social network theory has produced a wealth of paradigms to describe the nature and evolution of groups of people who interact, possibly in subgroups, with one another. Settings in which social network theory has been applied range from friend to corporations to political blocs to religious groups. Counterterrorism is one application of particular current importance, in which the notion that the network might have latent (unobservable) characteristics that are important to its evolution over time is especially germane. Currently, however, there is not good understanding of strengths and limitations of different models for the dynamics of social networks. The researchers on this project, drawn from the social sciences, statistics and applied mathematics, are constructing a conceptual and operational framework that allows the principled comparison of different models in multiple contexts. In addition to advances in theory and methodology, the framework enables social sciences researchers and other analysts to choose a model whose dynamic properties are most appropriate to each application.

5. OTHER REMINDERS

SAMSI: Information about workshops and other activities at SAMSI during 2004-05 is at http://www.samsi.info/200405/programs04-05.html