Ph.D. Using Big Data to Date Medieval Texts

Big Dating: Using Big Data to Date Medieval Texts

Applicants are sought for a fully-funded four-year Provost’s Project Award PhD doctoral award at Trinity College Dublin on the Big Dating project to start in September 2020 (or later, if Covid-19 does not permit it). The award comprises the student’s full tuition fees (EU or non-EU) and an annual stipend of €16,000. These doctoral awards are generously funded through alumni donations and Trinity’s Commercial Revenue Unit.

The Big Dating project explores quantitative and/or computational approaches to the language of medieval texts, particularly those from England in the long twelfth century, which evade the periodisation of English into ‘Old’ and ‘early Middle’. The successful applicant will be expected to devote up to 24 hours per month of work to this project, as well as complete a PhD thesis.

The topic of the student’s PhD thesis is not prescribed, but will be developed between the student and the supervisor. Possible approaches include (but are by no means limited to):

• Computer-assisted philological analyses of particular texts or groups of texts
• Cluster analysis of text languages to identify potential dating criteria
• Work towards developing an automated parser and/or lemmatiser for late Old English and early Middle English
• Bottom-up periodisations of Old and Middle English

Students interested in the doctoral award are invited to email the Principal Investigator, Dr Mark Faulkner (faulknem@tcd.ie) with expressions of interest by 22 May 2020. They may subsequently be invited to submit a CV, academic transcripts, a sample of written work and the names of two academic referees and asked to take part in a Skype interview. The final stage of the application process will involve the submission of a formal PhD proposal to Trinity.

The following may be considered the essential and desirable qualifications for the award:

Essential

• A Master’s (completed or in progress) in linguistics or Medieval Studies
• A first-class (or equivalent) undergraduate degree in a relevant subject
• Demonstrable communicative competence in English

Desirable

• Good working knowledge of Old and Middle English
• Experience using major medieval corpora and electronic resources (e. g. Dictionary of Old English Corpus, Linguistic Atlas of Early Middle English, Penn Parsed Corpus of Middle English Prose)
• Familiarity with the techniques of quantitative and/or computational linguistics