PhD Student Position: Empowering AI to Explore the Space of Reasons 80 %

vor 3 Wochen

Zürich, Zürich, Schweiz Universität Zürich Vollzeit
Digital Society Initiative
PhD Student Position: Empowering AI to Explore the Space of Reasons
80 % We invite you to apply for a four-year full-time PhD position in natural language processing with a highly innovative philosophical grounding. As a PhD student you will contribute to the research project «Empowering AI to Explore the Space of Reasons (Project AIR)» funded by the Digital Society Initiative (DSI) at the University of Zurich and lead by Dr. Reto Gubelmann. The DSI aims to promote cooperation between Zurich's higher education institutions in the field of digitalization and thus to strengthen Zurich as a center of research and business.

About the project
Human belief systems are made up of networks of claims that are connected by logical relationships of entailment and contradiction – the so-called space of reasons. Recent developments in natural language processing and the philosophy of language have opened a unique window of opportunity to explore this space of reasons. Project AIR seizes this opportunity, aiming to develop a novel hybrid method in natural language inference to build a data-grounded representation of this space of reasons. Following a radically open approach and building on aesthetic insights, the project will develop an interface to allow the general public to interact with (and thereby keep updated) our representation of the space of reasons. The specific PhD research topic will be determined based on the candidate's interests and expertise, in consultation with the supervisory team.
Your responsibilities
  • Develop a novel benchmark dataset for natural language inference
  • Contribute to developing and evaluating a novel Hybrid Method in NLI inspired by inferentialist ideas
  • Contribute to using this method to chart networks of inferentially connected claims in datasets
  • Analyze and discuss research findings and communicate results through publications and conference presentations
  • Support preparation of research proposals to national and international funding agencies
  • Support outreach activities that target the general public
Your profile
  • Very good master's degree in computational linguistics, computer science, AI, or a related discipline
  • Solid Programming skills (Python) as well as experience in using either PyTorch or TensorFlow
  • Enthusiasm for natural language processing and for natural language inference in particular
  • Interest in putting cutting-edge philosophical ideas into computational practice
  • Very good communication, interpersonal, and organizational skills
  • Excellent command of English, German competencies desirable, alternatively willingness to acquire them during the first two years of your PhD
What we offer
  • A 4-year research-focused position ideally suited to build a strong research profile
  • The chance to contribute to a potentially ground-breaking project combining philosophy of language and NLP
  • A highly innovative, interdisciplinary, and vibrant research environment with flat hierarchies
  • State-of-the-art facilities at one of the leading research universities of Switzerland
  • Strong support for your personal development and career planning
  • Option to apply for the DSI PhD Excellence Program - a unique interdisciplinary complementary doctoral program focused on digital transformations in society
  • Office space in the center of a vibrant, cosmopolitan city that regularly ranks as one of the cities with the highest quality of life in the world
  • Pay rates for PhD candidates are based on the standards set by SNSF
Place of workRämistrasse 69, 8001 Zürich, Switzerland
Start of employment Starting date: upon agreement (ideally 1st of August 2024)
Please submit your application by the 30 April 2024.
Your application should include: your CV, motivation letter (specify your research interests and how they relate to the topic of the research project), academic record (include additional education or coursework if applicable), contact information of two references and a writing sample (a paper or chapter from your Master's thesis).

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