Researcher in NLP. (this position is closed, keep an eye for new openings)
1 year, with the possibility of extension.
30 October, 2022.
Full-time, Hybrid (London, UK)
15 Nov 2022 (we are open to considering notice period requirements).
Nanu is a deep-tech start-up building a cognitive performance tool that will change how people engage in dialogue and develop skills during online meetings. We aim to have a massive societal impact by making better people, workplaces and better-performing businesses. We believe AI should enrich the common good and individuals' well-being, and we are working towards this goal.
We are building a plug-in for online conference systems (Zoom, Teams, Google Meet, Webex) that gives the speaker live- and post-meeting feedback about their conversational behaviour in the meeting. You will be part of a team that devises methods to translate empirical knowledge of behavioural sciences and organisational psychology into the predictive models that drive product functionality.
The successful applicant will be a computational linguist/NLP expert who will work with a software architect/engineer in a team. There will be feedback meetings with senior scientific advisors from various fields, including natural language processing, human-human and human-computer interaction, and behavioural and learning sciences. You will work with another computational linguist (the founder) to build language models that drive Nanu's functionality. The software engineer will deploy the models in a production environment, and you will coordinate with them to create a continuous flow of model updating into production.
Design and set up machine learning training pipelines in AWS.
Develop annotation schemes.
Fine-tune foundation models.
Train proprietary models.
Optimise models' performance.
Create language models integrating behavioural and learning sciences.
Collaborate with the software engineering team.
The ideal candidate will have the following:
A PhD or MSc in Natural Language Processing / Computational Linguistics with at least one peer-reviewed publication in the field;
Expertise in machine learning (applied to NLP), with experience in analysing and developing classical and deep learning models;
Experience in using libraries for NLP and deep learning, such as Tensorflow, Keras and Pytorch;
Experience in data annotation and data collection;
Enthusiastic, with a willingness to further improve skills and to create a supportive and positive working environment;
Capable of writing clear and comprehensive documentation.
Expertise in the following area is advantageous but not required:
Experience in multi-disciplinary research in behavioural and learning sciences.
We value creativity, curiosity, passion, persistence and life balance.
(this position is closed, keep an eye for new openings)