Principal NLP Scientist

The Position

As a Principal NLP Scientist your role will be to drive research initiatives on the cutting edge of technology. You will be working independently, managing complex matrix organisations.

As part of your role, you will:

Develop tools for relationship extraction/semantic similarities, summarization, Natural Language inference. Train neural network models for language understanding tasks and develop and fine-tuning of language models. Evaluate the performance of neural models and validate the accuracy of extracted knowledge. Work closely with multimodalities, multilingual ties, and multiagent. Support Scientific Intelligence and relevant parts of Digital Science & Innovation with knowledge enriching analysis results via natural language generation and GenAI. Actively guide and coach NLP Scientists in both professional development and project execution.

In your role you will be working closely with relevant Digital Science & Innovation teams to translate best-performance techniques into production. Part of it will entail setting technical directions and influencing the progression of initiatives across the early research organisation.

You will be responsible for presentation and reporting of scientific results and participate in line/digital projects progression with strong NLP and knowledge graph expertise as well as encourage, propose, and participate in projects boosting the use of advanced text mining and knowledge graphs.

Qualifications

We are looking for a highly motived person with project management skills and preferably with a PhD in Computer Science, AI, Computational Linguistics, Applied Mathematics, Physics or similar.

Apart from that, we expect our candidate to:

Good industry experience, preferably within pharma or biotech Strongly established experience with Natural Language Processing and Machine Learning technologies Experience with multimodal and/or multilingual language models. Profound knowledge of Deep Learning methods applied to NLP. Demonstrated track record of developing and applying NLP solutions applied on large text, preferably literature data.

The person who will thrive in the role is an effective communicator who has the desire to work with dispersed teams across multiple time zones. For this role attention to detail, stakeholder management skills and the ability to self-manage are key to succeed.

Having experience in the below would be considered an asset:

Publication record in top NLP / ML venues (e.g., NeurIPS, ICML, NACL, EMNLP, NAACL, TACL, AAAI, etc R&D and Life Science experience in the following: low-resource NLP, explainable NLP, development of language models incl. multimodality training R&D experiences on knowledge representation and reasoning and/or neural symbolic reasoning (BERT, RoBERTa, and GPT-4) Hands-on experience on production of NLP systems.

While for the time being it is an individual contributor role, we are open to receiving applications from profiles with people management experience.

About the Department

You will join 16 dedicated colleagues within the Novo Nordisk Scientific Intelligence department, which offers a centralised hub of external information as well as tools and technologies to extract data and insights to users across Novo Nordisk worldwide at headquarter and affiliates.

Our purpose is to provide modern digital solutions to the organisation and to ensure that research scientists have seamless access to quality information sources, state of the art technologies and professional information research tools supporting their needs in idea maturation, hypothesis validation, and increased disease and landscape understanding.

Scientific Intelligence is a part of a research area, Data & Knowledge Discovery (DKD), established to provide a modern data and knowledge excellence, drive external collaborations and access to emerging technologies in the digital space of drug discovery.

Data & Knowledge Discovery (DKD) is part of Digital Science & Innovation (DSI), established to drive digitalisation across R&ED. DSI participates in drug development projects across the value chain, from early discovery to pre-clinical development.