Senior Scientist, AI Applications - R&d Oncology

Johnson & Johnson Johnson & Johnson · Pharma · Spring House, PA +6

Senior Scientist role focused on developing and delivering AI/ML scientific applications for oncology drug discovery and development. The role involves working with LLMs, multimodal reasoning, agent memory architectures, and uncertainty quantification to accelerate research. Key responsibilities include hands-on technical delivery, prototyping, evaluation, and defining best practices for AI applications.

What you'd actually do

  1. The Senior Scientist will develop and optimize multimodal reasoning systems that integrate large-scale structured and unstructured data to derive actionable conclusions
  2. Build novel agent memory architectures to enable persistent knowledge retention and context-aware decision-making across extended discovery workflows
  3. Prototype and evaluate innovative approaches for uncertainty quantification and reliability assessment in AI-driven scientific reasoning
  4. Benchmark agent performance against human expert decisions and existing computational methods and demonstrate ability to publish results in leading journals and conferences
  5. Define and enforce engineering best practices across AI prototyping, including architecture patterns, documentation standards, quality gates, and reproducibility criteria

Skills

Required

  • Ph.D. degree in AI/ML or related field
  • 2+ years working experience
  • Sophisticated mathematics (Bayesian inference, uncertainty quantification, information theory, causal inferencing, graph neural networks)
  • Proficiency with open-source agentic frameworks (e.g., LangGraph, DSPy, mem0)
  • Proficiency with deep learning frameworks (e.g., PyTorch, Tensorflow)
  • Proficiency in Python

Nice to have

  • Understanding of drug discovery pipeline
  • Familiarity with biological data types
  • Experience in oncology research
  • Strong understanding of statistics
  • Familiarity with cloud hosting solutions (AWS and/or Azure)

What the JD emphasized

  • 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.)
  • Proficiency in one or more programming languages – preferably Python

Other signals

  • develop and deliver artificial intelligence (AI)/machine learning (ML) scientific applications
  • autonomous AI in oncology drug discovery and development
  • work with Large Language Models (LLMs)
  • reasoning agents faster, more accurate, and more reliable
  • multimodal reasoning
  • agent robustness and uncertainty
  • agent memory architecture
  • agent motivation frameworks
  • hands-on technical delivery of advanced analytic (AI/ML) Oncology R&D research
  • develop and optimize multimodal reasoning systems
  • Build novel agent memory architectures
  • Prototype and evaluate innovative approaches for uncertainty quantification and reliability assessment in AI-driven scientific reasoning
  • Benchmark agent performance against human expert decisions
  • define and enforce engineering best practices across AI prototyping
  • enable the scaling and deployment of tools aimed at the broader R&D community