We are seeking, starting 1 March 2024, a highly motivated candidate
for a 1-year postdoc position in the area of NLP and Linked Data within
the project TextEnt (Textual Entities in Time)
<https://www.unige.ch/lettres/humanites-numeriques/recherche/projets-de-la-chaire/textent>.

The successful candidate will be part of the Digital Humanities Unit at
the University of Geneva and jointly supervised by Simon Gabay
<https://www.unige.ch/lettres/humanites-numeriques/equipe/collaborateurs/simon-gabay>
(Textual Data, Computational Philology) and Nicola Carboni
<https://www.unige.ch/lettres/humanites-numeriques/equipe/collaborateurs/nicola-carboni>
(Linked Data, Graph Analytics).

Working conditions:

– Contract duration: 1-year contract
– Wage: CHF  78’625 (~82’000 €)
– Remote work: to be discussed
– Experience: PhD, 5 years maximum after the viva
– Starting date: March 1st

Tasks:

1. _Corpus building_: constitution of a corpus (c. 5,000 documents in
Historical French) from existing digital libraries, (ii) extraction of
the information with HTR, (iii) encoding in TEI. Data and HTR and layout
analysis models are provided.
2. _Geographic entities_: recognition and extraction from the retrieved
corpus of referenced entities (current, historical and imaginary). Data
and NER models are provided.
3. _Reconciliation_: development of a novel knowledge-driven pipeline
for linking identified geographical entities with their corresponding
historical entity retrieved by a list of public Knowledge Graphs (e.g.
Wikidata). To be built from scratch.
4. _Analysis_: development of methodologies for the quantification of
the impact in time of geographic entities through the analysis of their
spatial and historical dimension.

See this link for more details about the project, the skills required
and the application procedure:

Applications may be submitted before January 15th in either French
or English to simon.gabay @unige.ch and nicola.carboni @unige.ch and
should include:

– Curriculum Vitae, with a complete list of publications;
– a statement (max 2 pages) of why you are the ideal fit for the
position;
– One paper you (co-)wrote;
– additional documents to support your application (e.g. portfolio),
including the names and contact details of two references.