Full-time PhD position at IT University of Copenhagen, under the umbrella of the Pioneer Centre for AI, Denmark, starting in Summer-Autumn 2023.
Topic: Modelling compositional language structures across languages. The origin of language development of human beings can at least be traced back to two sources: the survival needs for communication and the unique wiring of human brains. The two factors can co-develop with each other through life-span. Nevertheless, languages from the whole world are with tremendous diversity. Yet, given the fact that all human brains share very similar structures and connection patterns, which presumably afford for similar ways to encode and decode information from the external world, there likely exist some hidden common structures, like some word orders or numbers of phonemes in a language, that are shared at least within, or even across, language families. An important constraint for these similar structures comes from the theory that the brain is processing language embodied in all our senses and via processing streams that are also involved in a range of other cognitive functions from specific motor control up to general problem-solving. This suggests that language comprehension and production, in fact, developed on top of existing information processing schemes, which in turn might have similarly shaped how the different language families have developed. A particular mechanism that was recently hypothesized to give rise to the structure of the brain’s sequence processing is temporal compositionality and chunking, which seemingly operate on language sequences as well. With this PhD project, we want to identify and describe the specific, latent temporal encoding structures that may constrain the temporal features of spoken language. In this project, the candidate will study structure patterns in spoken language and investigate how to build a model that can extract temporal characteristics of speech across different languages. Since the project is interdisciplinary, active collaboration within the Pioneer Centre for AI, as well as with experts in computational neuroscience and developmental psychology in Germany and Japan are planned. Application details: The ideal candidate should have a Masters in Computer Science, Computational Neuroscience, Computational Linguistics, Developmental Psychology, Cognitive Science or related fields, as well as a strong interest in interdisciplinary research, at the intersection of Natural Language Processing, Machine Learning, and Psycholinguistics. The salary scale will be in accordance with the Ministry of Finance’s agreement with the Danish Confederation of Professional Associations for a full-time position. As a PhD Student at the Pioneer Centre for AI you will have extraordinary access to computing resources, international researchers across disciplines, courses and events at the centre and meaning collaboration with industry, the public sector etc. ITU is a teaching and research-based tertiary institution concerned with information technology (IT) and the opportunities it offers. The University offers an informal working environment, a varied everyday life, and a highly motivated, competent, diverse, and international faculty. Copenhagen has a strong educational system, a rich cultural life, universal healthcare, good childcare, and a well-functioning infrastructure. The city is also among the world’s most liveable cities according to the Economist Global Liveability Index. Candidates will work together with Stefan Heinrich ([email protected]) and Barbara Plank ([email protected]), and are encouraged to get in contact for details. Link to further application information: https://www.aicentre.dk/phd-openings - and application link: https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181550&DepartmentId=3439&MediaId=5 Application deadline: 01 April 2023, at 23:59 CET. -- *************************** Dr. Stefan Heinrich Assistant Professor Computer Science Department IT University of Copenhagen https://stefanheinrich.net/ ***************************
