[Humanist] 32.37 postdocs, data scientist, PhD studentships (Aix - Marseille)

Humanist Discussion Group willard.mccarty at mccarty.org.uk
Tue May 22 08:29:43 CEST 2018

                  Humanist Discussion Group, Vol. 32, No. 37.
            Department of Digital Humanities, King's College London
                Submit to: humanist at lists.digitalhumanities.org

        Date: Mon, 21 May 2018 18:51:21 +0000
        From: "Cecile J. Armand" <carmand at stanford.edu>
        Subject: Job announcements

Call for applications – ERC ENEP-China project

1 Postdoc position in computing
1 Postdoc research position (NLP)
1 Data scientist position
3 Ph.D. positions

The project ENEP-CHINA proposes a step-change in the study of modern China reliant upon scalable data-rich history. It will deliver precise historical information at an unprecedented scale from heretofore untapped sources – as well as reshaping the analysis of existing sources – to create a new dimension in the study of the transformation of elites in modern China. It will deploy an array of cutting-edge digital methods — including data mining, sampling, and analysis within an integrated virtual research environment. To establish the validity of this approach, the project focuses on the three urban areas (Shanghai, Beijing/Tianjin, Canton/Hong Kong) that had the most profound impact on the course of modern Chinese history. 

The key issue that the project will address is breaking through existing limits of access to historical information that is embedded in complex sources and its transformation into refined, re-usable and sustainable data for contemporary and future study of modern China. This project borrows substantially from the concepts and methods, especially quantitative methods and network analysis from sociology and political science. For the analysis of textual corpora, it draws on the procedures and applications developed in linguistics and literary studies to explore large corpora of unstructured texts. Finally, it implements the most advanced tools and methods designed in computing, especially data mining and machine learning.

The job descriptions are attached as PDF and could also be found at the following link: https://virtualshanghai.hypotheses.org/documents.

Best regards,

Cécile Armand

Cecile J. Armand
Postdoctoral Scholar
Department of History
Center for Spatial and Textual Analysis
Stanford University

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