Teaser Text

Applications are invited for a fully funded PhD candidature on the use of formal methods to enhance the efficiency, transparency and the understanding of Large Language Models.While large language models (LLMs) have proven successful in many areas of Natural Language Processing, they suffer from high data and resource usage and display limited generalization capacity in tasks that humans excel at. In this PhD project you will have the opportunity to investigate how formal methods can help in developing more efficient and more transparent models for Natural Language Understanding.The specific project content is to be decided between the applicants’ interest and the expertise of the supervisor (dr. Gijs Wijnholds: https://gijswijnholds.github.io ). Topics for the PhD may include (but are not limited to):

• Using logical methods to define task-relevant constraints on LLM finetuning;
• Combining neural and symbolic approaches to solve Natural Language Understanding tasks;
• Assessing the generalization capacity of LLMs in the context of reasoning tasks and/or model probing;
• Evaluation of Natural Language Understanding models in the presence of ambiguity and/or annotator disagreement;
Understanding multilingual Natural Language Inference in Vision-Language Models.

In this position you are expected to develop your own research line; as such we ask for a brief research proposal (max. 1 page) which outlines a project you would like to work on.You will be embedded in the Leiden Institute of Advanced Computer Science (LIACS) at Leiden University, supervised by dr. Gijs Wijnholds and prof. dr. Suzan Verberne.

What you will do

• Conduct original research in the field of Natural Language Understanding, focusing on the combination of formal methods and Large Language Models;
• Publish and present scientific work at international journals and conferences;
• Engage in collaboration with other researchers within and outside LIACS;
• Assist in relevant teaching activities.

Where you will work

The Faculty of Science is a world-class faculty where staff and students work together in a dynamic international environment. It is a faculty where personal and academic development are top priorities. Our people are committed to expand fundamental knowledge by curiosity and to look beyond the borders of their own discipline; their aim is to benefit science, and to contribute to addressing the major societal challenges of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and environmental sciences. The research activities are organised in eight institutes. These institutes offer eight bachelor’s and twelve master’s programmes. The faculty has grown strongly in recent years and now has more than 2.300 staff and almost 5,000 students. We are located at the heart of Leiden’s Bio Science Park, one of Europe’s biggest science parks, where university and business life come together. For more information, see www.universiteitleiden.nl/en/science and http://workingat.leiden.edu/

The Leiden Institute of Advanced Computer Science ( LIACS ) is the Artificial Intelligence and Computer Science Institute in the Faculty of Science of Leiden University. We offer courses at the Bachelor and Master of Science level in Artificial Intelligence, Computer Science, ICT in Business, Media Technology, and Bioinformatics. According to an independent research visitation, we are one of the foremost computer science departments of the Netherlands. We strive for excellence in a caring institute, where excellence, fun, and diversity go hand in hand. We offer a clear and inviting career path to young and talented scientists with the ambition to grow. For more information about LIACS, see http://www.cs.leiden.edu

What you bring

• A master’s degree in computer science, Artificial Intelligence, Computational Linguistics, Logic, or a related field;
• Substantial knowledge of Natural Language Processing;
• A strong interest in multidisciplinary approaches combining formal tools with neural models;
• Excellent analytical and problem-solving skills;
• Knowledge of deep learning architectures, specifically Large Language models;
• Excellent research skills;
• Excellent writing and presentation skills;
• Excellent programming skills (Python).

What we offer

• We offer a full-time 1-year term position for initially one year. After a positive evaluation of the progress of the thesis, personal capabilities and compatibility, the appointment will be extended by a further three years. This contract falls under the CLA of Dutch Universities;
• A salary between € 3.059,= and € 3.881,= gross per month, based on a full-time appointment (38 hours) (Payscale P);
• A holiday allowance (8%), an end-of-year bonus (8,3%), and an attractive pension scheme at ABP;
• Full reimbursement of public transport commuting costs for home-to-work travel;
• Flexible working hours: as a standard, you are entitled to a minimum of 29 leave days on the basis of a full-time working week of 38 hours; you can also save for extra leave, for example by working 40 hours a week, and in this way accrue an extra 96 leave hours, or exchange 96 leave hours for a 36-hour week.
• Lots of options when it comes to secondary employment conditions; we can, for example, discuss options for a sabbatical or paid parental leave. Within our terms of employment individual choices model, you can exchange leave days and/or salary for benefits such as an advantageous sports subscription and bicycle scheme;
• If your work allows it, hybrid working is possible within the Netherlands;
• A home-working allowance (day and internet allowance) and attention for good workplaces. The University will also provide you with a laptop.

What we value

Diversity and inclusion are core values of Leiden University. Leiden University is committed to becoming an inclusive community which enables all students and staff to feel valued and respected and to develop their full potential. Diversity in experiences and perspectives enriches our teaching and strengthens our research. High quality teaching and research are inclusive.

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