AbbVie's Peptide Therapeutics team is looking to accelerate peptide drug discovery by adopting and developing generative AI methods. They aim to identify and develop novel algorithms and pipelines to guide and optimize AI-enabled hit generation strategies using their proprietary peptide synthesis platform.
Requirements
- Proven experience developing deep learning approaches for peptide generation and peptide drug design
- Experience with protein structure modeling, design, or prediction algorithms, spanning physics-based to deep learning architectures
- Fluent in Linux command-line, python, and version control (git)
- Demonstrated record of research excellence in machine learning as evidenced by conference presentations (e.g. NeurIPS) and journal publications
- Applied experience in a quantitative science (e.g., Chemistry, Biology, Biochemistry, etc.)
- Extensive experience working with large chemical and biological datasets, including graph, sequence, and structure-based data
- Hands-on experience building and training models, applying transfer learning, and/or fine-tuning models using deep learning frameworks (such as PyTorch)
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
- Formulate conclusions and design follow-on experiments based on multidisciplinary data
- May initiate new areas of investigation that are scientifically meaningful, reliable, and can be incorporated directly into a research or development program
- Author of publications, presentations, regulatory documents and/or primary inventor of patents
Other
- Present results at internal and external scientific conferences
- Routinely demonstrate scientific initiative and creativity in research activities
- Understand and adhere to corporate standards regarding code of conduct, safety, appropriate handling of materials, controlled drug and radioactive compounds, GxP compliance, and animal care where applicable
- Direct mentorship of others
- Ability to work collaboratively on projects with multiple contributors
