Senior Molecular Data Scientist - Biologics

Key Skills

Aartificial intelligence, Data science techniques, Design, Effective communication skills, Machine learning techniques, Pandas, Python Programming, Scikit-learn

Job Description

Key responsibilities

• Develop predictive models for biologics design as well as SAR analysis and visualization methods and integrate them into the in house in silico pipeline to enable multi-objective compound design and data-driven decision making
• Apply predictive models for biologics design, including developability engineering and experimental design of high-throughput variant libraries
• Review technology landscape and build external collaborations with key partner in the AI field for biologics

The ideal candidate has a general curiosity and excellent track record within drug discovery, molecular modelling, and/or machine learning technologies, can identify and address key project challenges, can collaborate well within a multidisciplinary environment, has a positive attitude towards challenges, takes the initiative for driving projects, and can stay on top of things in a dynamic working environment.

Qualifications

• A PhD degree within a computational chemistry or biology discipline, such as Computational Chemistry, Molecular Modelling or Bio-/Cheminformatics, and 2+ years of drug discovery experience in relevant pharma/biotech R&D environment or comparable track record of post graduate experience in academia.
• Strong track record in the development and application of AI/ML for de novo design and/or compound property predictions, preferably for biologics
• Broad knowledge of cheminformatics, bioinformatics, and QSAR methods and experience with the development of related data analysis pipelines and visualizations
• Fluent in Python, data-workflow tools, and data science packages like scikit-learn and pandas

As a person you have excellent interpersonal skills with an ability to respond to shifting priorities in a dynamic setting, a positive attitude towards challenges, and great communication skills to thrive in a multidisciplinary, collaborative working environment. In addition to the above qualifications experience with modelling software programs such as Rosetta and Schrodinger and/or MOE would be advantageous.

About the Department

The Protein Engineering department is part of Novo Nordisk’s Computational Drug Design (CDD) area where we apply and develop state-of-the-art capabilities in structure-based modelling and AI/ML approaches for drug design. Scientists within CDD collaborate seamlessly with teams across the globe to invent better molecules faster. With an unbiased approach to drug modalities, in-house access to the newest screening techniques, and world-class experimentation, we have a wealth of opportunities to impact our pipeline and ultimately save and improve patient lives. We work in multidisciplinary, highly collaborative discovery teams both locally and across Novo Nordisk’s global network to 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 Protein Engineering team is focusing on the design of biopharmaceutical proteins such as protein minibinder and protein replacement therapies, using Molecular Modelling and Machine Learning approaches. 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 Denmark, United States and the United Kingdom, we strive to deliver the latest advancements in protein therapeutics to benefit patient health and global medicine.

Contact

For further information, please contact Mark Watling (wmwl@novonordisk.com)