Postdoctoral Researcher UU – A digital discourse analysis of the Republic of Letters’ idealistic language, 1400-1800 (deadline 11 June 2018)

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The Department of History and Art History of Utrecht University seeks to appoint a three year Postdoctoral position to conduct research on “A digital discourse analysis of the Republic of Letters’ idealistic language, 1400-1800”. This research is a sub-project of the ERC Consolidator project “Sharing Knowledge in Learned and Literary Networks (SKILLNET): the Republic of Letters as a pan-European Knowledge Society”, led by Dr. Dirk van Miert.

In the sub-project, the Postdoc will study the frequency and spread of words and concepts that reference or connote the ideal of sharing knowledge, or the lack thereof, or the antonyms thereof, in a large and multilingual body of early modern texts: primarily letters, but also learned journals, historia literaria, table talks and all sorts of adversaria. The project is devoted to creating chronological and semantic maps of the main identitary concepts which held the Republic of Letters together and to seeing whether these notions change over time or differ according to period, region, discipline, language, religion, social status, and gender. The candidate will have to prepare a large set of texts currently available in various formats for discourse analysis, mine these texts digitally, visualise the results and analyse them in the context of a cultural history of knowledge. The aim is to test the generally accepted idea that the civil society of the Republic of Letters connotes sodality, cooperation, exchange and the common good and to chronologically, geographically and socially nuance and diversify our picture of the history of the Republic of Letters. The outcome of the project consists of at least five articles. These may be subsequently collected into a monograph. All publications will be published in Open Access.

A successful candidate should preferably have:

  • a PhD degree in early modern history of knowledge;
  • demonstrable experience with NLP and digital text mining;
  • affinity with History of Concepts/Begriffsgeschichte;
  • knowledge of Latin, French and German;
  • excellent command of English, both written and orally;
  • a publication record that fits with her career stage;
  • capacity to work both as a creative and independent researcher and as part of a team.

We offer a temporary position (1.0 FTE) for one year, which after a satisfactory evaluation will be extended by another 24 months (3 years in total). Start date is from 1 September 2018 onwards, but no later than 1 January 2019. The gross salary – depending on previous qualifications and experience  – ranges between €3,238 and €3,475 (scale 10/11 according to the Collective Labour Agreement Dutch Universities) gross per month for a full-time employment. Salaries are supplemented with a holiday bonus of 8 % and a year-end bonus of 8.3 % per year. We offer a pension scheme, (partly paid) parental leave, collective insurance schemes and flexible employment conditions (multiple choice model). More information is available at: working at Utrecht University.

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Aanvullende informatie
A brief summary of the entire research project is available here.
Enquiries can be made to Dirk van Miert, via An extended research description is available upon request.

Written applications should address each of the criteria mentioned under qualifications and include the following documents:

  • cover letter;
  • curriculum vitae;
  • a memo stating proposals as to how conduct this research (max. 1000 words);
  • copy of relevant diplomas and grades;
  • copy of a recent academic publication (max. 30 pages) or a recent paper;
  • digital copy of the dissertation;
  • names and contact details of two referees.

Candidates who make the shortlist will be invited for an interview. These may be conducted in person in Utrecht or via Skype. Dates for interview will be set in the first week of July 2018.

Please use the application button below to apply. The application deadline is June 11 2018.


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