On behalf of Katie McDonough, I’m just bouncing on details of a new 18-month maps Research Associate position, that may hopefully interest some on this list.

Further details at: https://cezanneondemand.intervieweb.it/turing/jobs/research_associate_digital_history_12738/en/
Closing Date: 21 March.

Thanks,

Chris



Applications are now being accepted for an 18-month Research Associate in Digital History on the Machines Reading Maps project based at The Alan Turing Institute<https://www.turing.ac.uk/> in London. We are open to people with varied qualifications and previous experience (see job description for examples).

Please share with colleagues who may be interested in working on a collaborative, trans-Atlantic project at the intersection of computational humanities, GIScience, and GLAM-related data science. There is a growing community of humanities and GLAM researchers affiliated with the Turing and the person in this role will have the chance to collaborate and learn with them as well as with staff at the cultural heritage institution project partners (USC Libraries, Library of Congress, National Library of Scotland, British Library). Project and role descriptions are copied below the signature.

Full details here:
https://cezanneondemand.intervieweb.it/turing/jobs/research_associate_digital_history_12738/en/
Applications must be received by midnight (UK) March 21.

Please reach out with any questions - [log in to unmask]<mailto:[log in to unmask]>.

Many thanks,
Katie McDonough

Project Description:
‘Machines Reading Maps’ (MRM) is an AHRC- and NEH-funded research project based both at The Alan Turing Institute and the University of Southern California that aims to change the way that humanists, heritage professionals, and the general public interact with maps. They constitute a significant body of global cultural heritage, and are being scanned at a rapid pace in the US and UK. However, most critical investigation of maps continues on a small scale, through close ‘readings’ of a few maps. Individual maps communicate through visual grammars, supplemented by text. But text on maps is an almost entirely untapped source for understanding how knowledge of place is constructed. Investigating map content at scale can teach us about what has been preserved and omitted in the cartographic record. Such knowledge is a key starting point for understanding why using map text to enrich collection metadata may be advisable (when collection records lack any, or only the most superficial, geographic or locational information) or potentially harmful (for example, when map text replicates colonial power structures).

We envision a future where map collections can be searched based on their spatial content, similar to the way that digitised newspaper collections enable full-text searching across scanned pages. This project contributes to reversing the fortunes of historic map collections. MRM will enable researchers and cultural institutions to generate and analyze map text data across collections and institutions, contributing to metadata creation and decolonization efforts, and enhancing accessibility and discoverability of un- or minimally-catalogued sheets.

Advancing software tools for handling new types of maps is essential to making text extraction a method that can be used in libraries and archives around the world. MRM generates data from scanned map collections and builds community among map and data curators, metadata and digital scholarship specialists, historians, and geographic information and data scientists. Working with partners at the National Library of Scotland, British Library, and the Library of Congress, this work unites research questions about the spatial experience of industrialization in 19th-c. Great Britain and social change in US cities during the 20th c. with GIScience methods for processing historical maps at scale.

Role Description:
Machines Reading Maps is looking for a Research Associate (18 months) to work on creating and reading map text datasets. The candidate may be a historian with a background in spatial analysis or who has used maps as primary sources, or a digital humanist, GLAM professional, or data scientist with experience working with computational methods to process map collections or other geospatial data. Our goal is to find a colleague who can think critically about scanned map collections and how collecting text from maps can transform humanities research.

You will work closely with the UK PI (Dr. Katherine McDonough) as well as the US Project Director (Deborah Holmes-Wong, USC) and US Co-Director (Prof. Yao-Yi Chiang). There will be opportunities to collaborate with the whole team, cultural heritage partner organisations, as well as the humanities and data science community at the Turing. Beyond this, you will build community with international researchers and GLAM professionals with an interest in our methods. You will play an active role in shaping and sharing our method for unlocking text on maps, including data acquisition, developing and writing up research articles, and teaching GLAM and humanities audiences how to use these methods.

This is a collaborative, trans-Atlantic research project, and so it is crucial that you enjoy working with others (synchronously and asynchronously) and are responsive within an iterative research process. You will have an opportunity to develop a research project using map text data, under the mentorship of the UK PI and other project leaders. Opportunities and support for professional development will be available within the Turing and externally.
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