Recorded Future announces an Industrial PhD Student position in computational linguistics. The position is tied to the research project ‘Interpreting and Grounding Pre-trained Representations for Natural Language Processing’. The project is a collaboration between Linköping University, Chalmers University of Technology, and Recorded Future AB, and is a part of the WASP Graduate School.
The Project
Building computers that understand human language is one of the central goals in artificial intelligence, and also a core part of how Recorded Future is building a system that constructs a digital twin of the world by automatically analyzing text in multiple languages.
A recent breakthrough on the way towards this goal is the development of neural models that learn deep contextualized representations of language. However, while these models have substantially advanced the state of the art in natural language processing (NLP) for a wide range of tasks, our understanding of the learned representations and our repertoire of techniques for integrating them with other knowledge representations and reasoning facilities remain severely limited. To address these gaps, this project will develop new methods for the interpretation, grounding, and integration of deep contextualized representations of language.
The Position
This position is as an employee of Recorded Future, where we expect you to devote 80% of your time to your PhD studies, and 20% to working with project within the company’s R&D organization. Your PhD project will be aligned with the projects you work with within the company.
You will be enrolled in the PhD student program at Chalmers University of Technology or Linköping University.
You are expected to start your position sometime between September 1st and December 31st, 2020.
This is a two-stage call. In the first phase, projects were applied for and evaluated. Approved projects then continued to this, the second phase, where each university open calls for PhD positions. Information about AI/MLX Collaboration Projects can be found in the initial call: https://wasp-sweden.org/positions/wasp-collaboration-projects-within-ai-mlx/