Are you passionate about Sign Language Linguistics? Are you proficient in at least one sign language yourself? Do you have experience collecting, annotating, and analyzing sign language data? And do you have a solid background in formal syntax and semantics? We are seeking a PhD candidate to investigate syntactic and semantic properties of questions across a broad range of sign languages through fieldwork and collaboration with an international network of sign language linguists.

The PhD position is part of a newly established collaboration between the University of Amsterdam and Meta AI (formerly Facebook AI) Research. The project focuses on the development of natural language processing and machine learning methods for automated detection of misinformation online.

Do you combine a knowledge of natural language semantics with that of experimental methods and their statistical analysis? Are you an expert in the use of causality and/or bias in Artificial Intelligence? Do you have a track record of publishing in leading journals in Logic, Language and/or Artificial Intelligence? Are you an inspiring teacher who is competent to teach a wide variety of courses in the areas of logic and natural language analysis, as well as Human(e) AI? Do you have an excellent command of both English and Dutch?

Main reading: Peters, Jonas, Dominik Janzing, and Bernhard Schölkopf. 2017. Elements of Causal Inference: Foundations and Learning Algorithms. The MIT Press.

For the next meeting, we have to:
- Work on the problems of Chapter 3.5 "Problems" (pp. 39-41)For programming, prefer R.Submit solutions to the drive file [link in our website], so that others can access them for discussion.
- Read Chapter 4 "Learning Cause-Effect Models" (pp. 43-70)

At the beginning of the meeting, Matt will give a 10' presentation on the main arguments of the Dawid (2021) and Janzing et al. (2016) papers in the "Suggested Readings" [see website].

When mathematicians and logicians hear the term 'intuitionism' they often think about the law of excluded middle, weak proof systems, and Heyting's formalisation of his teacher's philosophy. In this talk we will look at Brouwer's philosophy and mathematics of intuitionism, tracing some of the philosophical underpinnings, and motivating his mathematical results with contemporary mathematical tools. In it, we emphasise Brouwer's attempt to undermine the place of logic in the foundation of philosophy, replacing it with a special notion of 'intuition'.