Sr Scientist I, AI/ML

AbbVie

Ludwigshafen, Germany

Job Description

AbbVie seeks a knowledgeable, self-motivated, and creative scientist with demonstrated impact in AI/ML applications for computational chemistry/drug discovery. The selected candidate will join our Computational Drug Discovery group within the Discovery Research organization.

The candidate will have the opportunity to develop and advance AI/ML technologies at the heart of computer-aided drug design. The candidate should have broad experience with computational techniques with a focus on the state-of-the-art methods in machine learning applied to chemical and biological data. The key responsibilities of this position are to identify, develop, optimize, validate, and deploy innovative methods for molecular generation, drug-target interaction prediction, and modeling that leverage artificial intelligence and machine learning models to enhance molecular design capabilities. The candidate should have a working knowledge of chemistry and the ability to work collaboratively with a broad variety of disciplines including other members of our internal computational chemistry and cheminformatics groups to accelerate drug discovery from hit identification through candidate selection.

You will have access to state-of-the-art modeling, simulation, and machine learning technologies as well as computing infrastructure, and be able to leverage rich collections of data to accelerate drug discovery in a fast-paced and creative environment.

Qualifications

BS, MS, or PhD in Chemistry/Computer Science/Machine Learning/Cheminformatics/Chemical Engineering or related education with typically 10+ years (BS), 8+ years (MS), or 0-3+ years (PhD) and experience developing machine learning models related to chemical and biological data;
Expertise with developing, implementing and deploying programs and computational solutions employing Machine Learning/Deep learning and Cheminformatics;
Expertise in AI/ML-enabled molecular generation, pose generation, and/or affinity prediction are preferred;
Ability to implement, debug, and maintain computational tools in common programming languages (Python, etc., …) and proficiency with cloud computing capabilities;
Strong analytical and problem-solving skills with demonstrated ability to think critically and creatively, and provide solutions both individually and collaboratively with internal experts to develop and optimize the computational discovery infrastructure including cloud resources;
Excellent ability to communicate clearly and concisely with colleagues and collaborators including an ability to explain complex ideas to non-specialists;
Familiarity with KNIME, Pipeline Pilot, or other automation interfaces;
Familiarity with modern deep learning architectures including GNN, CNN, RNN, Transformer, GCNN and MPNN, and machine learning paradigms such as generative models, GAN, and active learning;
Experience with deep learning platforms such as Pytorch, Tensorflow, or Keras;
Strong programming skills in Python and experience with data science stack including numpy, pandas, scikit-learn, and other related scientific libraries.

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