Postdoctoral Research Opportunity: Postdoctoral Researcher in Language Model Interpretability and Digital Humanities – University of Basel
Postdoctoral Research Opportunity: Postdoctoral Researcher in Language Model Interpretability and Digital Humanities – University of Basel
Institution: University of Basel
Unit: Digital Humanities Laboratories (DHLabs)
Research Group: contralab
Project: A Philology of Probabilistic Texts: The Problem of Interpretation in Artificial Intelligence
Position: Postdoctoral Researcher (80%)
Funding: Swiss National Science Foundation
Appointment Type: Fixed-Term, 80%
Duration: 48 months
Initial Contract: 2 years
Extension: Further 2 years expected after positive review
Location: Basel, Switzerland
Residence Requirement: Residence in the trinational Basel region is mandatory
Expected Start Date: March 1, 2027, or by arrangement
Salary / Remuneration: According to University of Basel and SNSF postdoctoral salary guidelines; exact amount not specified in the vacancy
Application Deadline: November 25, 2026
Overview of the Opportunity
The Digital Humanities Laboratories at the University of Basel invite applications for a Postdoctoral Researcher in Language Model Interpretability and Digital Humanities within the four-year SNSF-funded project “A Philology of Probabilistic Texts: The Problem of Interpretation in Artificial Intelligence.”
The project investigates how large language models interpret historical texts, with a particular focus on how eighteenth-century concepts shift across genres and decades and how fine-tuned open-weight models represent those changes.
The successful candidate will lead the project’s computational work while collaborating closely with scholars in literary history, media studies, science and technology studies, machine learning, NLP, and the philosophy of language.
Research Focus
The project explores:
Large language model interpretation
Historical and literary corpora
Diachronic semantic change
Language model fine-tuning
Model interpretability
Digital humanities
NLP
Machine learning
Historical texts
Philosophy of language
Literary theory
Benchmark development
The project will also produce:
An annotated corpus of model divergences
An open benchmark for diachronic semantic understanding
A taxonomy of model misreadings of historical texts
Key Responsibilities
The successful candidate will:
Prepare and validate historical corpora.
Assess OCR quality and metadata related to genre and date.
Fine-tune open-weight language models on period texts.
Use continued pretraining and parameter-efficient methods such as LoRA.
Build an attribution pipeline using token-level SHAP.
Compare interpretability results with probing and causal-intervention methods.
Conduct systematic model tests and controlled prompting experiments.
Collaborate with literary historians on analysis.
Lead the technical development of the benchmark release.
Prepare documentation, baselines, and a public leaderboard.
Lead or co-author papers for NLP and Machine Learning venues.
Co-author humanities-oriented publications within the project.
Essential Qualification
Applicants must have a doctorate by the time of appointment in one of the following or a related field:
Computer Science
Natural Language Processing
Computational Linguistics
Machine Learning
Digital Humanities
Computational Humanities
Related computational disciplines
Applicants should also have:
Hands-on experience training and fine-tuning transformer language models.
Strong Python skills.
Experience with PyTorch and Hugging Face.
Experience using GPU clusters.
Experience with interpretability methods and/or benchmark development.
Ability to design controlled and reproducible experiments.
Strong research-software practices.
Strong written and spoken English.
Serious interest in historical texts, literary theory, and philosophy of language.
Preferred Qualifications
Desirable experience includes:
Historical or OCR-derived text.
Semantic change detection.
Annotation studies.
Public datasets or open-source tools.
Publications in NLP or Machine Learning venues.
Feature attribution.
Probing.
Activation patching.
Sparse autoencoders.
Engagement with:
Literary theory
Historical materialism
Hermeneutics
Structuralist linguistics
Historical linguistics
Knowledge of German.
Research Environment
The postdoctoral researcher will be based within contralab, led by Prof. Dr. Ranjodh Singh Dhaliwal.
The position is co-supervised by:
Prof. Dr. Ranjodh Singh Dhaliwal
Dr. Juan Luis Gastaldi, Sorbonne University and ETH Zürich
The project provides access to the University of Basel’s sciCORE scientific computing centre and GPU infrastructure.
Teaching in the Digital Humanities programme may also be arranged.
Application Checklist
Applicants should submit:
Academic Curriculum Vitae
Submitted as a separate file
Single PDF containing:
Cover Letter – maximum 2 pages
One example of research
The research sample may be:
A paper or chapter
Only the first 25 pages will be considered
Or the full URL of:
A code repository
Dataset
Digital project
The URL should be provided as plain text rather than a clickable hyperlink.
Applicants should also state in the cover letter whether they currently hold, or expect to hold, another employment alongside this position.
Shortlisted candidates may later be asked to provide letters of recommendation.
Nature of Appointment
Postdoctoral Research Position
80% Appointment
Fixed-Term
Total Duration: 48 Months
Initial Contract: 2 Years
Expected Extension: Additional 2 Years following positive review
Position supports further academic qualification and development of the candidate’s own research profile
Important Dates
Application Deadline: November 25, 2026
Expected Start Date: March 1, 2027, or by arrangement
Initial Contract: 2 years
Total Project Appointment: 4 years at 80%
All applications received by November 25, 2026 will receive equal consideration regardless of submission date.
How to Apply
Applications must be submitted through the University of Basel online recruitment portal.
Contact:
contralab@unibas.ch
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