Job: postdoc ABM Ancient Egypt

The following job might be of interest to readers of this blog:

Postdoctoral Position : Agent-Based Modeling of Social Complexity in Ancient Egypt

An interdisciplinary (social science, computational archaeology, and machine learning) two (2) year postdoctoral research fellowship for agent-based modeling and simulation is currently available at the Department of Computer Science, University of Cape Town.

The postdoctoral fellow will work on an interdisciplinary agent-based modeling (ABM) and simulation project that investigates the emergence of social complexity in early Egypt. The project proposes to develop the ABM as an experimental computational platform for studying and analyzing complex system behaviour, in this case, the evolution of societal complexity. The ABM will be used to design experiments that examine the social dynamics of early Egypt, including the emergence of entrenched inequality, urbanism, social hierarchy, networks, and ideology of kingship. The goal is to explore how the Egyptian state emerged as a
result of the meaningful actions of individuals pursuing their own interests within the particular environmental conditions of the Nile
Valley in the fourth millennium BC, as well as compare this system to similar case studies in social complexity in Africa more broadly.

As part of the process of developing the ABM, the fellow will be expected to conduct research on the modeling of emergent complexity in agent-based models of ancient societies, including the application of evolutionary machine learning to simulate adaptive behaviour. Ideally the ABM design principles will take inspiration from the relevant social complexity literature and prevailing theories of emergent complexity.  However, the exact focus of the project will be jointly decided by the postdoctoral fellow and supervisors.

The candidate will have the opportunity to collaborate with the interdisciplinary network of researchers at the Evolutionary Machine
Learning Group, University of Cape Town, the Department of Ancient Studies, Stellenbosch University, and the Department of Archaeology, University of Cape Town. In addition to research, candidate is expected to co-supervise graduate students within this network of researchers.

  • PhD (or nearly completed) degree in computational archaeology, computer science, or a closely related field.
  • Good programming skills (Java, Python, Net Logo or other agent-based modeling languages).
  • Excellent communication skills, in both spoken and written English, and the ability to work independently.
  • Expertise in agent-based modeling and simulation.
  • Some expertise in evolutionary machine learning would be advantageous.
  • Candidates with a background in computational archaeology who are willing to acquire machine learning expertise during the postdoc, are encouraged to apply.

Deadlines and More Information:

Starting date is flexible: From February 1, 2020.

Applications will be evaluated on a first-come-first-serve basis, and will continue to be received and reviewed from December 1, 2019 until the position is filled.

Representing Networks, University of Cologne, 5-6 June 2019

This event will be of interest to readers of this blog. The program looks great and I can definitely recommend you attend this. Don’t forget to register before 31 May.

via HNR and Danijela Stefanović:

Representing Networks: Past and Present

Workshop at the University of Cologne,

5-6 June 2019

Please register at by 31 May

For more information, see


Wednesday, 5 June

17:30               Welcome and registration

18:15               Public key note lecture:

From Microhistory to the Global Network – The World of the Treasurer Senebi (Danijela Stefanović, University of Cologne, University of Belgrade)

Reception in the rooms of Egyptology, sponsored by Uschebti e.V.

Thursday, 6 June

09:30               Welcome and registration

09:45-10:00     Introduction

10:00-11:30     How Many Networks? Representing Dynamic Social Change Using Archaeological Network Methods (Fiona Coward, Bournemouth University)

An Ivory Diaspora: Digitizing Exchange & Production Networks in the Medieval World (Sara Ann Knutson, University of California, Berkeley)

11:30-11:45     Coffee break

11:45-12:30     Casting a Wide Net: The Distant Reading of Archival Documents from Babylon (Maarja Seire, University of Leiden)

12:30-14:00     Lunch break

14:00-15:30     From Networks to High-dimensional Geometry and Back (Allon Wagner, Tel-Aviv University, University of California, Berkeley)

Representing Credit and Kinship in the 19th Century: Between Exploration and Simulation (Martin Stark, ILS- Research Institute for Regional and Urban Development)

15:30-15:45     Coffee break

15:45-16:30     Representing the Community of Ptolemaic Pathyris as Network Models: Possibilities and Limitations (Lena Tambs, University of Cologne)

16:30-17:00     Closing discussion

Data Ninjas VS Spaghetti Monster

puntoThere are some new kids on the network Science playground, and you better stay friends with them because they are here to kick ass. They call themselves the Data Ninjas. Introducing: “six degrees of spaghetti monsters“, the blog by the Leuven network researchers working with the Trismegistos database. The blog currently contains some interesting resources: books, links, blogs and the like. Soon the Data Ninjas will share results of their research so keep an eye on the blog. In the meantime, no better description of the ninjas than the one they provide on the blog:

All right folks! You found us! This means one of two things: either you’re friend/family/foe and you’re curious about what we’re up to (thanks for playing, better luck next time), or you’re seriously into SNA and you’re hoping to actually find some useful stuff here. We should pause here and warn you though: we are NOT SNA guru’s, despite us being worshipped by our department colleagues. We are, first and foremost, historians, lovers of all things antique (preferably Graeco-Roman in Egypt). And proud of it! About a year ago then, we started to explore the subtle science of social network analysis. We’ve come a long way since then, but we’re basically still rookies compared to the many die-hard sociologists, mathematicians, computer wizzes and all out there. RESPECT.
So basically what we’re aiming at with this blog is to let the world know what your tax money is spent on. Actually it’s just a very narcissistic self-promotional format. Science communication and valorization are the new buzz words when it comes to fellowship and grant applications, so we doing just that here. But buried deep down we still have an altruistic streak, so we’d also like to help out other self-taught, or wannabe self-teaching SNA’ers and to provide a forum where we can exchange thoughts and “experiments” (sounds pretty sciency huh? ¯\(°_⊙)/¯). We’re planning on posting some entries on the books and courses we’ve been using to get started, as well as on the software we’ve been playing with. And we’ll obviously keep you up-to-date on our research. We hope to present some AWESOME results here soon! Of course, this blog will be very history-oriented, so not all of our posts will be equally relevant for those of you who are working in other fields. But the beauty of SNA is that its basic principles are applicable to almost all types of networks, so we hope you’ll still enjoy our musings. And don’t hesitate to leave remarks, suggestions, questions, praise, cheers, jokes, your phone number, … We solemnly swear to reply as swiftly and as best as we can.
And we’re up to no good. Obviously.

“leaderless revolutions” in modern Egypt and … the past??

I just read this fascinating blog post by Zeynep Tufekci, assistant professor in sociology at the University of Maryland, Baltimore county. She states that through the democratic nature of the recent revolution in Egypt a hierarchy emerged. A fundamentally leaderless situation gave rise to popular leadership. According to the author this can be explained by the “rich get richer” effect, and she illustrates this with how People on Twitter using the hashtag ‘Jan25’ shows a scale-free power law. Apparently, those people tweeting about the revolution that have alot of followers will end up getting ever more followers. They have become the (digital) leaders of a headless revolutionary event. I find it interesting how this hierarchy and its immediate effects must have been the result of a critical mass of influence reaching a turning point, leading to revolutionary events.

Obviously Twitter is only one medium through which ideas can be spread, and in no way does the “rich get richer” effect explain WHY the revolution happened. What were the individual motivations that led to this large-scale event? What the scale-free model does imply, however, is that the event could not have taken place without these individuals and their actions, their decisions to follow increasingly popular charismatic (albeit digital) figures.

Could this perspective help us understand past revolutions?

Obviously ideas spread much slower in the past than in the present. But that does not mean that revolutions happened any slower or less spontaneous. How could we explore past revolutions through the material remains that we examine as archaeologists? I would be very interested in seeing how changes in material culture attest of a scale-free pattern. A perfect example is Bentley and Shennan’s work on Linear Bandkeramik in Germany. They showed that the patterns on these vessel evolved according to a scale-free power law, where popular motifs were expected to become ever more popular and more influential in future motif design. What fascinates me about this kind of research is that it does not incorporate any measure of originality in innovation. Motifs or ideas might not have been all that revolutionary, for example, but for some reason they became popular and widely adopted. Through them revolutions emerged, more as a result of their relation to other things/people/ideas than their inherent qualities. Still, the question of why this scale-free structure emerges and shapes revolutions remains unanswered. And what about truly revolutionary ideas? Does their adoption show a scale-free structure? And if not, is that really the reason why they did not catch on?

Create a free website or blog at

Up ↑