Job: funded PhD digital classics Lausanne

The below job will be of interest to readers of this blog.

Via Matteo Romanello:

The DHLAB at EPFL in association with the Institut d’archéologie et des sciences de l’antiquité of the University of Lausanne invites applications for one full-time, fully-funded PhD position within the EPFL PhD program in Digital Humanities, working at the intersection between Computer Science and Classics. 
The successful candidate will develop their own research project around the following topics: semantic information extraction by combining text-based and image-based methods; alignment and document analysis of scholarly publications (19c – 21c) characterised by complex layouts and rich visual grammars; and the development of a representation model for texts with a complex textual tradition. 
The PhD thesis will be part of the research project “How does a classical hero die in the digital age? Using Sophocles’ Ajax to create a commentary on commentaries”, funded by the Swiss National Science Foundation (SNSF) and led by Matteo Romanello (University of Lausanne).
  • Applicants should hold a master’s degree in Computer Science or Digital Humanities.
  • Experience with natural language processing/information extraction (including machine learning approaches to it) is mandatory. Some familiarity with textual criticism is desirable. PhD candidates will further develop their analytical and methodological skills by attending the EDDH doctoral school.
  • Fluent English; French and/or Ancient Greek/Latin is an asset. The dissertation can be written in English or French.
  • Interest in working in a collaborative, interdisciplinary and international environment.
  • Candidates of all nationalities are invited to apply; applications from women are especially welcome.
What we offer:
  • workplace: EPFL/UNIL campus
Starting date: 1st October 2020
Duration: 4 years
Supervisors: Matteo Romanello (UNIL) and Frederic Kaplan (EPFL)
Terms of employment: Fixed-term at 100% work rate. EPFL offers internationally competitive salaries and generous research support.
Deadline for applications: April 30, 2020
Contact: For questions and/or expressions of interest, contact Matteo Romanello
How to apply: via EPFL doctoral school online application (please note that only completed applications will be reviewed). For further information about applying for a PhD at EPFL see PhD admission criteria & application.

LAC session Unravelling entangled pathways

This session at the Landscape Archaeology Conference (2-5 June in Madrid) sounds great and will be of interest to readers of this blog.

Deadline 14 February!

Via Laure Nuninger:

We are pleased to invite you to participate in the session: #027 Unravelling entangled pathways. Debating new approaches to study the interaction of past movement and settlement systems, which will be held at the LAC2020 conference in Madrid (ES), 2-5 June 2020. 
How does it work? 
This is an open session with a slightly different format. The session will be introduced by a keynote contribution. This keynote contribution will be pre-circulated to the presenters a month before the conference in order to share the concepts and approaches that we intend to discuss. The contributors to the session are expected to reflect upon this in their own presentations, in order to support a shared and open discussion at the end of the session. 
How to participate 
Please send us an e-mail, and submit your contribution electronically via the online submission system (LAC) by the given deadline of February 14th, 2020.
Please feel free to ask any other questions you might have!
Best regards
The organisers: Laure Nuninger,  Rachel Opitz, César Parcero-Oubiña, Thibault Saintenoy, and Philip Verhagen
#027 Unravelling entangled pathways

Understanding the motivations and travel patterns of past societies allows for a better analysis of land use dynamics because movement underlies the organization of a wide variety of landscape features. Movement left physical or intangible (memory, stories) traces that are difficult to recover because they are intertwined and create a complex archaeological picture over long periods of activity. Movement in archaeology is studied through diverse approaches (observational field work, remote sensing detection, network analysis, spatial analysis and modelling, agent-based modelling and simulation…). The ontological interoperability of the data created through these approaches is uncertain. The challenges of making these data compatible is particularly salient, given that much of the data involved is digital, in the context of the FAIR data principles. Consequently new paradigms to reconstruct the logical assemblage that constitutes systems of movement are needed.

This session provides a forum to discuss the theoretical and methodological implications of analyzing past movement, in particular within the context of settlement system studies. How do we conceive the relationship between space and movement ? How do we elaborate datasets to study movement within the landscape ? How do we use and structure various datasets in our analyses of movement flows and their relationship with the landscape and settlements? How do we conceive, as archaeologists, the idea of pathways entanglement, related to their accumulation over time?

To approach these issues it is necessary to clarify:

  • The landscape archaeological frameworks we use to create data about or to conceive past movement.
  • The way we are interpreting empirical evidence of movement about the landscape which has to be presented in detail: how do we treat built roads ? trails ? stairs ? or other path features ? how do we recognize them as pathways ?
  • Our analytical approaches to the study and interpretation of past movement: what kind of data and knowledge do we use to study a movement flow, a network or a meshwork? How might computational modelling as a emulation/simulation of movement help to disentangle and complete the empirical data picture?
  • Our idea of validation of models of movement from theoretical and computational points of view, and in relationship to the settlement system.

This session aims to consider these questions within the framework of the FAIR data principles, building towards the goal of creating inter-compatible ontologies for past movement studies. This session further aims to bring together diverse perspectives to discuss and compare the paradigms, data, and analyses applied in different contexts. We therefore invite papers based on case studies from any region. We particularly encourage case studies presented within the framework of a transcultural approach, including comparisons across multiple regions.  Papers can present advanced ontological approaches or more generally address their own reflections and experiences related to the themes of this session.

Session Keywords: pathways; movement; meshwork; network; settlement system

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.

The Connected Past 2020 in Aarhus

Delighted to announce the next instalment of The Connected Past, this time in Aarhus Denmark. The call for papers deadline is 15 March, submit your abstracts to

Conference website


September 24-25, Aarhus University

Artefactual Intelligence

Preceded by a two-day workshop 22-23 September (more information to follow).

Call for Papers now open (deadline 15 March)

Abstracts (max. 250 words) should be sent to

Before March, 15th 2020*

Please include your name, affiliation, and your choice of session format (20 minute thematic presentation or 10 minute work-in-progress presentation)

*The scientific committee will seek to communicate its decision before mid-April 2020

Our keynote speakers are Marcia-Anne Dobres on agency in archaeology and Juan Barceló on Artificial Intelligence in archaeology.

Computational models used by archaeologists are becoming increasingly complex. We create and tackle ever larger datasets, include more parameters and make machines learn by themselves. Recent approaches to network theory in archaeology, and the historical sciences more generally, have embraced agents, agency and practice theory. But where does this leave objects? Since the earliest days of the discipline, objects have been at the core of the archaeologist’s enquiry. However, until recently, objects were left heavily undertheorised. With the advance of object-related theories, such as ANT or the New Materialism approaches, agency is extended not just to humans but to the objects and materials they handle as well. Does this mean that digital archaeologists and historians are to move from Artificial Intelligence to Artifactual Intelligence? And if so, how?

Being a community of scholars interested in recent theoretical and methodological innovations in archaeology and the historical sciences, the Connected Past Conference provides a forum for presenting and discussing ongoing work on the intersection between archaeology,  history, digital approaches and theory. The conference will be preceded by a two-day practical workshop (limited capacity, open call for participants to follow soon).

This year’s conference focuses specifically on the topic of artefacts, human and material agency, artificial and artefactual intelligence and their place within archaeological and historical network studies. In addition, we also welcome presentations on any topic related to archaeological or historical network research and complexity science.

We invite abstracts for 20-minute presentations on these and related topics for consideration to the scientific committee. In addition, there will be a session on general topics related to network science in archaeology and the historical sciences. We equally welcome abstracts for 10-minute presentations on work-in-progress.

Conference organisers:

Lieve Donnellan
Rubina Raja
Søren Sindbæk
Tom Brughmans

Get in touch!

Mediterranean summer school complex networks

This summer school will be of interest to readers of this blog.

We are calling for applications from students and young researchers in Network Science for the 7th edition of the Mediterranean School of Complex Networks, which will take place in Salina (Italy), 5-12 Sep 2020.

Early applications are expected before 31 March 2020 (no payment required at this step). Seats are limited to 50 attendants.

Since its first edition in 2014, our School trained more than 230 early-career researchers in Network Science from 4 continents. All details about previous editions, location, important dates and travel are available at the official website:
You might also want to watch the School teaser:

Please, note that for the youngest researchers (no more than two years from their PhD completion) who are members of the Complex Systems Society, we will grant up to two scholarships covering the registration fee.

We kindly ask you to circulate this call among your peers, students and other potentially interested applicants.

Best wishes,
Manlio De Domenico & Alex Arenas
MSCX Directors

Jobs: 6 postdocs Social Network Analysis

Readers of this blog might be interested in these jobs (Via Humanist).

Deadline for applications 19/02/2020.

We are currently recruiting 6 Post-doctoral Research Fellows with
expertise in social research methods to work within the Trento Center
for Social Research Methods.

Computational/digital sociology and social network analysis
Two post-doctoral research fellows for researchers with experience in
computational/digital sociology and social network analysis. This
includes, among others:
·       computational methods for “statistical learning”, using R or Python,
·       design and analysis of experiments, including field and online
experiments and use of digital devices (e.g. smartphones, wearables),
·       advanced social network analysis and recent developments in
ERGM, SAOM/SIENA, multilevel and multimodal networks, large-scale networks,
·       The quantitative analysis of texts through text mining and the
use of techniques such as LDA (Latent Dirichlet Allocation), CTM
(correlated topic model) and LSA (latent semantic analysis)
·       the simulation of social phenomena with agent-based modelling (ABM).

For more details, please

The application deadline is: 19/02/2020, 12:00 (noon), CET.

CFP: computational approaches to Roman economy, EAA

At this year’s EAA there will be a session very close to my research interests: computational approaches to the Roman economy.

Be sure to submit your abstracts via the EAA website.

Deadline: 13 February 2020.

From abacus to calculus. Computational approaches to Roman Economy


The study of the Ancient economy is an interdisciplinary endeavour on the intersection of archaeology, classics and historical economy, that tries to reconcile evidence from written and material sources across a wide range of regions, with different degrees of data availability and diverse traditions of studying these sources. The ‘Roman economy’ is a concept that has many possible interpretations, and accommodates a wide range of case studies from estimating production capacities and local trade networks to Empire-wide investigations on demography, wealth distribution and trade volumes.


With the advent of ever-growing and better accessible digital datasets, increasing computer power and more sophisticated computer science approaches to data mining and modelling, the analysis of the Roman economy is now entering a new stage. We can now start to meaningfully connect disparate data sets and use formal computational modelling to explore their potential, e.g., to elucidate the mechanisms that led to the different economic trajectories in the various parts of the Empire, or to reconstruct the social and political networks that enabled economic growth.


In this session, we invite speakers to present studies of the Roman economy that have used computational modelling as a tool to bridge the gap between fragmented, disconnected data sets and interpretive frameworks. This can include but is not limited to:

– statistical modelling,

– data mining,

– agent-based modelling and simulation,

– network analysis,

– spatial modelling

– machine learning,

– or a combination of approaches.


These can be applied to any topic relevant to Roman Economy: demography, land use, trade networks, craft production, finance, administration and others. We are also welcoming more theoretically oriented papers on the role of computational modelling in historical economic studies of the Roman Empire and comparative case studies from other periods.


Job: Postdoc computer vision and machine learning applied to cultural heritage

This job will be of interest to readers of this blog. Computer vision and machine learning applied to cultural heritage, archaeology and digital humanities.

Deadline 15 February.

Via Dr Arianna Traviglia.

PostDoc on Computer Vision and Machine Learning (CCHT@Ca’Foscari) – [ Postdoc ]

Added on: 26/09/2019 – Expires on 15/02/2020

The IIT Centre for Cultural Heritage Technology (CCHT@Ca’Foscari) of the Istituto Italiano di Tecnologia (IIT) in Venice has been established for researching and promoting new technologies and approaches for recording, documentation, analysis and preservation of Cultural Heritage in a broad sense (artistic, archaeological, archival, historical heritage). A strongly interdisciplinary infrastructure, the Centre combines expertise from computing and conservation sciences domains, integrating these competencies to foster cutting-edge research.

CCHT@Ca’Foscari is currently seeking to appoint a Senior PostDoc (i.e. minimum of 3 year experience outside PhD program) with a solid background in Computer Vision and Machine Learning approaches and methods, to be applied to Cultural Heritage applications. The search seeks at consolidating CCHT expertise especially in one or more of the following applications (not comprehensive list): 3D artefact digitisation and recording, document and text analysis, artefact classification and remote sensing data processing.

The selected candidate will join an interdisciplinary team of researchers, contributing to the development of next generation Computer Vision and Machine Learning approaches applied to the Cultural Heritage and, more broadly, Digital Humanities domains.

Required qualifications:

  • a Ph.D. in computer science or related field (with specialisation in either Computer Vision or Machine Learning) and +3 years CV/ML experience outside PhD, OR demonstrated similar experience;
  • Knowledge of programming languages, e.g. Python, MATLAB etc.;
  • Experience in grant proposal preparation at National and/or European level;
  • Interest in cultural heritage (applications to archaeology, art, artefact studies etc) and, more broadly, Digital Humanities
  • Proven interdisciplinary collaborations with scientific staff or stakeholders in the Cultural Heritage /Digital Humanities fields.
  • Good communication skills and ability to cooperate;
  • Proficient in English language (written and oral).

Desirable skills:

  • Strong track record of research publications in top tier conferences and journals (e.g. CVPR, ICCV, ECCV,  ICML, NIPS, PAMI, JMLR, etc.).
  • Experience in supervising or co-supervising Ph.D. students or postdocs;
  • Knowledge of OpenCV, PCL and Open3D libraries;
  • Experience on Deep Learning algorithms and relevant platforms (e.g. TensorFlow, PyTorch, Theano, Caffe);

The successful candidate will be offered a competitive salary commensurate to experience and skills.

The call will remain open until the position is filled but a first deadline for evaluation of candidates will be on February 15th, 2020. Please send your application to quoting “CCHT Computer Vision and Machine Learning Senior PostDoc BC 77512” in the e-mail subject. Your application must include (as separate documents):

  • a detailed CV
  • a research statement, expanding on current and past research
  • 3 representative publications.
  • name and contacts of two referees

Fondazione Istituto Italiano di Tecnologia – IIT ( – was founded with the objective of promoting Italy’s technological development and further education in science and technology. In this framework, IIT’s scientific program is based on the combination of basic scientific research with the development of technical applications, a major inspirational principle. The research areas cover scientific topics of high innovative content, representing the most advanced frontiers of modern technology, with wide application possibilities in various fields ranging from medicine to industry, from computer science to robotics, life sciences and nanobiotechnology.

Istituto Italiano di Tecnologia is an equal opportunity employer that actively seeks diversity in the workforce.

Please note that the data that you provide will be used exclusively for the purpose of professional profiles’ evaluation and selection, and in order to meet the requirements of Istituto Italiano di Tecnologia.

Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security.

Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 – email: dpo[at] )



CFP: “Network Approaches to Near Eastern Archaeology and History” (Boston ASOR)

This session will be of interest to readers of this blog.

Deadline 15 February.

CALL FOR PAPERS: “Network Approaches to Near Eastern Archaeology and History” (Boston ASOR)
We invite submissions for the session “Network Approaches to Near Eastern Archaeology and History” at the 2020 ASOR Annual Meeting in Boston (November 18–21, 2020). This is a member-organized session chaired by Steven Edwards (Centre of Geographic Sciences), Ioana Dumitru (Johns Hopkins), and Christine Johnston (Western Washington University). Papers should be 20 minutes in length.

Session Description: This session will explore current applications of network analysis across a range of case studies spanning the Near East. From the rise of social and economic inequality to the development of interregional trade systems, network analysis provides archaeologists and historians with a suite of statistical tools to explore patterns in large, complex datasets. The contributions in this session highlight how network analysis is being used to tackle challenging and important questions of archaeological and historical significance, and showcase the amenability of network approaches to engaging with diverse types of data—whether archaeological or textual in nature.

Information for the call for papers can be found here:

The submission deadline for abstracts is February 15, 2020. Please note that you must be a member of ASOR in good standing and must register for the Annual Meeting in order to submit an abstract and participate in the meeting.

If you have any questions about the session or about the submission process please contact us at, or

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