Senior AI Scientist I

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.

Job Description

Purpose:

Nimble recognizes the potential power of AI/Machine Learning approaches to accelerate the discovery of novel peptide therapeutics, and we believe that the ability of our platform to generate massive data sets uniquely positions Nimble to be the leaders in this area. We are seeking a highly motivated Machine Learning Scientist to join Nimble to help drive our efforts to develop Machine Learning methods to accelerate peptide drug discovery. The successful candidate will be responsible for identifying and developing novel algorithms and pipelines and collaborating extensively with computational and experimental scientists to iteratively optimize the approach to Generative-AI enabled hit discovery.   

Responsibilities:

• Develop machine learning and computational chemistry methods to enable discovery of peptides and/or peptide containing scaffolds that bind to target proteins.
• Develop group to leverage various computational chemistry tools and machine learning architectures to accelerate design of peptide-based molecules.
• Lead deployment of machine learning algorithms across various therapeutics areas.
• Build data sets and develop novel strategies to quantify model performance.
• Present results at internal and external scientific conferences.
• Routinely demonstrates scientific initiative and creativity in research or development activities.
• Highly autonomous and productive in performing laboratory research or method development, requiring only minimal direction from or interaction with supervisor.
• Formulate conclusions and design follow-on experiments based on multidisciplinary data.
• May initiate new areas of inv