[agents] Postdoctoral Position : Agent-Based Modeling of Social Complexity in Ancient Egypt : University of Cape Town

[gnitschke at cs.uct.ac.za]

Postdoctoral Position : Agent-Based Modeling of Social Complexity in
Ancient Egypt : University of Cape Town, South Africa

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.

Requirements:

* 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.

Contact for more information: Geoff Nitschke (gnitschke at cs.uct.ac.za).


Geoff Nitschke

Director – Evolutionary Machine Learning Group
https://people.cs.uct.ac.za/~gnitschke/research.html

Department of Computer Science, University of Cape Town

South Africa