The Position

We are seeking an exceptional department head for the biological machine learning team based out of the London/Oxford area who will contribute to cutting-edge research in the analysis of biological data and integration of different data modalities.

We are specifically interested in establishing a more integrated methodological framework for the target and biomarker discovery in early research, spanning from the analysis of our in-vitro, high throughput perturbative screening platforms, to AI/statistical analysis within genomic and translational research and to augment the analysis with various types of background knowledge in an optimal manner.

In this role, you will work directly with colleagues within computational biology, human genetics, computational drug design and computational precision health to drive the development and implementation of state-of-the-art AI/ML techniques and the computational pipelines associated with these. Thus, the position requires close collaboration with our data science and machine learning colleagues across global sites.

As part of your role, you will:

• Lead a team of scientists within AI/ML for the analysis of various biological data types, including genetic/genomic, epi-genetic data, transcriptomic data, imaging and biomedical knowledge graphs.
• Drive the establishment of an integrated computational framework to support target and biomarker discovery in R&ED.
• Drive the use and integration of real-world evidence.
• Drive collaboration with academia and industry, with particular focus on the knowledge quarter in London and communicate findings and results to stakeholders through presentations, reports, and scientific publications.
• Help set the strategy in R&ED for the use of generative AI to decrease time from target identification to first human dose.
• Stay current with the latest research and advancements in deep learning, representation learning, and multi-modal data integration.

You will be expected to come at least 2 times per week to our London office. 5-15% overnight travel is required.

Qualifications

We are searching for a candidate who meets the following criteria:

• PhD within AI/ML or bioinformatics.
• Several years of professional experience within pharma/biotech industry, including some years within people leadership.
• Broad experience in establishing and running computational drug discovery pipelines, delivering value to research projects.
• Considerable experience in stakeholder management and priority alignment in a multi-disciplinary context.
• Extensive experience in multi-modal data integration, bioinformatics, statistical genomics and epi-genomics, representation learning, large language models and/or graph neural network methods.
• Proven track record of using real world evidence / biobank data for drug discovery.
• Proficiency in Python and experience in the PyTorch deep learning libraries.
• Experience in modern version control and continuous integration/testing systems, such as GitLab/GitHub.
• Strong written and verbal communication skills.

About the Department

The Machine Intelligence department is part of our AI and Digital Research (AIDR) area, where we apply and develop state-of-the-art capabilities in representation learning, multi-modal data integration, and AI/ML approaches for target and biomarker discovery and drug design. Our scientists collaborate seamlessly with teams across the globe to invent better molecules faster, impacting our pipeline and ultimately saving and improving patient lives. Working in multidisciplinary, highly collaborative discovery teams both locally and across our global network, we invent novel medicines by applying advanced computational techniques and developing innovative computational methods. We also engage in external collaborations to ensure access to cutting-edge research and technology.

The Multi-modal Representation Learning scientists in Machine Intelligence focus on the analysis of various biological data, such as genomic and transcriptomic data, protein sequence and structure, images, and more. We specialize in biological representation learning, using both traditional bioinformatic tools as well as large language models, biomedical knowledge graphs, graph neural networks, multi-modal diffusion models, and decoder-only generative models to integrate different data modalities and enhance our understanding and predictions. We collaborate closely with our experimental colleagues in early research to improve and accelerate the design of new drug candidates. With a team of scientists located in multiple countries, we strive to deliver the latest advancements in multi-modal analysis to benefit patient health and global medicine.

Working at Novo Nordisk

We are a proud life-science company, and life is our reason to exist. We’re inspired by life in all its forms and shapes, ups and downs, opportunities, and challenges. For employees at Novo Nordisk, life means many things – from the building blocks of life that form the basis of ground-breaking scientific research, to our rich personal lives that motivate and energise us to perform our best at work. Ultimately, life is why we’re all here - to ensure that people can lead a life independent of chronic disease.

Contact

Please submit your CV, cover letter, and a list of relevant publications via our careers site. We look forward to reviewing your application and exploring the potential for you to contribute to our dynamic and innovative team!

Deadline

Please apply before 1st July.

We encourage you to apply early, as our Talent Acquisition team engages with candidates on an ongoing basis.

We commit to an inclusive recruitment process and equality of opportunity for all our job applicants. 

At Novo Nordisk we recognize that it is no longer good enough to aspire to be the best company in the world. We need to aspire to be the best company for the world and we know that this is only possible with talented employees with diverse perspectives, backgrounds and cultures. We are therefore committed to creating an inclusive culture that celebrates the diversity of our employees, the patients we serve and communities we operate in. Together, we’re life changing.