We seek a highly motivated researcher with a strong track record in NLP. The ideal candidate should be able to demonstrate broad knowledge of neural architectures as applied to core NLP tasks. The position presupposes a PhD degree or equivalent in Natural Language Processing, or in Computer Science with a clearly NLP-based thesis.

The successful candidate will be invited to participate in the definition of the scientific profile for this position, jointly with one or more post-doctoral ‘supervisors’ from the LTG permanent staff. The project will be expected to both be compatible with and complement current research at LTG, preferably creating points of contact with others in the group. Current prominent research activities at LTG include sentiment analysis (for Norwegian and English), detection and analysis of negation and hedges (for English and Norwegian), parsing into graph-structured representation of meaning, multi-lingual probing of linguistic knowledge in neural architectures, and in techniques for model adaptation to low-resource domains and languages.

A one-year equivalent of the position will be dedicated to teaching and related activities. The language technology group is responsible for several MSc- and BSc-level classes on various aspects of natural language processing, machine learning and programming. Teaching experience and pedagogical skills will be given weight in the evaluation, in particular of machine learning approaches to NLP.

For more information about the Language Technology Group (LTG) at IFI.

Postdoctoral fellows who are appointed for a period of four years are expected to acquire basic pedagogical competency in the course of their fellowship period within the duty component of 25 %.

The main purpose of a postdoctoral fellowship is to provide the candidates with enhanced skills to pursue a scientific top position within or beyond academia. To promote a strategic career path, all postdoctoral research fellows are required to submit a professional development plan no later than one month after commencement of the postdoctoral period.


University of Oslo


The Faculty of Mathematics and Natural Sciences has a strategic ambition is to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

The candidate must have a PhD or other corresponding education equivalent to a Norwegian doctoral degree in Natural Language Processing. Doctoral dissertation must be submitted for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defence are eligible for appointment.
The successful candidate has comprehensive knowledge of contemporary neural techniques and architectures in NLP, including for example (contextualized) embeddings, convolutional and recurrent networks, neural language modeling, and transfer and multi-task learning. Both a theoretical understanding of these approaches and practical experience (for example using frameworks like Keras, DyNet, PyTorch, or TensorFlow) are desirable.
Desire to perform high-quality research
Eagerness to learn
Interest and ability to work in an international research team

Language requirements:

Fluent oral and written communication skills in English

Educational level:

Ph. D.

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