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 atwww.abbvie.com. Follow @abbvie onX,Facebook,Instagram,YouTube,LinkedInandTik Tok.

Purpose:

We are seeking a highly motivated Peptide design and Machine Learning Scientist to join AbbVies 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 includingnon-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 ascollaborating closelywith both computational and experimental scientists to guide and optimize ourAI-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 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
• 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

• Bachelors Degree or equivalent education and typically 10 years of experience, Masters Degree or equivalent education and typically 8 years of experience, PhD and no experience necessary.
• 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
• Thorough theoretical and practical understanding of relevant scientific disciplines
• 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)
• Experience using cloud computing, high-performance computing, or GPU clusters
• Ability to work collaboratively on projects with multiple contributors
• High level of autonomy and productivity in laboratory research or method development, requiring minimal supervision

Preferred:

• Experience developing deep generative approaches for cyclic peptide drug design
• Experience developing deep generative approaches for peptides with non-canonical amino acids
• Experience developing novel strategies to quantify model performance, especially for diffusion, flow-matching, and transformer-based models
• Experience contributing to drug discovery efforts

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state orlocal law:

• The compensation range described below is the range of possible base pay compensation that the Companybelieves ingood faith it will pay for this role at the timeof this posting based on the job grade for this position.Individualcompensation paid within this range will depend on many factors including geographic location, andwemayultimatelypaymore or less than the posted range. This range may bemodifiedin thefuture.

• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick),medical/dental/visioninsurance and 401(k) to eligibleemployees.

• This job is eligible toparticipatein our short-term incentiveprograms.

Note: No amount of payis considered to bewages or compensation until such amount is earned, vested, anddeterminable.The amount and availability of any bonus,commission, incentive, benefits, or any other form ofcompensation and benefitsthat are allocable to a particular employeeremainsin the Company's sole andabsolutediscretion unless and until paid andmay bemodifiedat the Companys sole and absolute discretion, consistent withapplicable law.

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.

US & Puerto Rico only - to learn more, visithttps://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html

Company Name: AbbVie
Website: https://careers.abbvie.com/en/job/s...
Company Description:

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