Senior AI Scientist - Peptide Design

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:

We are seeking a highly motivated Peptide design and Machine Learning Scientist to join AbbVie’s Madison Peptide Therapeutics team.  In this role, you will help drive our adoption and development of generative AI methods to accelerate peptide drug discovery.  Our team uses a proprietary peptide synthesis platform capable of synthesizing bespoke peptide libraries consisting of millions of unique peptide sequences, that can incorporate a variety of amino acids including non-canonical amino acids.  The platform enables rapid empirical evaluation of computationally designed peptide sequences, giving us a unique advantage in this field.  The successful candidate will be responsible for identifying and developing novel algorithms and pipelines, as well as collaborating closely with both computational and experimental scientists to guide and optimize our AI-enabled hit generation strategies.

Responsibilities:

• Develop machine learning and computational chemistry methods to enable discovery of peptides and/or peptide-containing scaffolds that bind to target proteins
• Lead efforts 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 therapeutic areas
• Build data sets and develop novel strategies to quantify model performance
• Present results at internal and external scientific conferences
• Routinely demonstrate scientific initiative and creativity in research activities
• Formulate conclusions and design follow-on experiments based on multidisciplinary data
• May initiate new areas of inves