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Job Function: Data Analytics & Computational Sciences
Job Sub Function: Data Science
Job Category: Scientific/Technology
All Job Posting Locations: Cornellà de Llobregat, Barcelona, Spain, Madrid, Spain
Job Description
Johnson & Johnson Innovative Medicine (J&J IM) is recruiting for the role of Senior Scientist – AI Agent Systems for Drug Development. This position has a primary location of Barcelona, Spain. The secondary location is Madrid. This is a hybrid role.
J&J IM develops treatments that improve the health and well-being of people worldwide. Research and development areas encompass oncology, cardiovascular and retina disorders, immunology, and neuroscience. Our goal is to help people live longer and healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about J&J IM, please visit https://www.jnj.com/.
The Machine Intelligence (MI) team within Data Science and Digital Health (DSDH) AI/ML is looking for a mission-driven Scientist to help develop the future of autonomous AI in drug discovery and development. You'll work with Large Language Models (LLMs) and sophisticated data science techniques, harnessing massive datasets spanning scientific literature, omics, and biomolecular knowledge. Your work will directly accelerate how we discover therapeutics and advance them to clinical trials—making reasoning agents faster, more accurate, and more reliable. Key focus areas include multimodal reasoning, agent robustness and uncertainty, agent memory architecture, and agent motivation frameworks.
Key Responsibilities:
* Develop and optimize multimodal reasoning systems that integrate large-scale structured and unstructured data to derive actionable conclusions
* Build novel agent memory architectures to enable persistent knowledge retention and context-aware decision-making across extended discovery workflows
* Prototype and evaluate innovative approaches for uncertainty quantification and reliability assessment in AI-driven scientific reasoning
* Serve as a domain expert within the field by articulating to team members emerging approaches and methodologies within the AI/ML with a clear understanding of their practical applications
* Benchmark agent performance against human expert decisions and existing computational methods and demonstrate ability to publish results in leading journals and conferences
Required qualifications:
* A Ph.D. degree in AI/ML or related field (e.g., computer science, machine learning, data science, applied mathematics, statistics) with at least two (2) years working experience
* Knowledge in sophisticated mathematics areas such as Bayesian inference, uncertainty quantification, information theory, causal inferencing, graph neural networks, etc.
* Proficiency with open-source agentic frameworks (e.g., LangGraph, DSPy, mem0, etc.) and deep learning frameworks (e.g., PyTorch, Tensorflow, etc.)
* Proficiency in one or more programming languages – preferably Python
* Positive and motivated demeanor with the ability to work both independently and in a diverse, multi-disciplinary team
Preferred (\"nice-to-have\") qualifications:
* Understanding of drug discovery pipeline and familiarity with biological data types
* Experience in chemical engineering, protein engineering, or manufacturing-related fields
* Strong understanding of statistics and applicable methods to validate model performance
* Familiarity with cloud hosting solutions (ex. AWS and/or Azure)
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