Translational AI Researcher — Multi-Modal Neurodegeneration

Job Description Johnson & Johnson Innovative Medicine is seeking a Translational Post Doctoral Researcher — Agentic AI for Neurodegeneration for a 2-year fixed-term position. This position can be located in either Raritan, NJ; Titusville, NJ; Spring House, PA; San Diego, CA; or Cambridge, MA. No fully remote option. The next frontier in neurodegeneration research is integrating insights across the data we already have at scale with agentic AI in ways that were previously not possible. Whole slide pathology, PET and MRI imaging, multi-omics, and longitudinal clinical records each offer a different lens on the neurodegenerative diseases; brought together, they tell a story no single modality can. This integration challenge is reshaping how we build agentic AI systems for drug discovery and how we evaluate them. Traditional benchmarks were composed for single-modality reasoning. Evaluating whether an AI co-scientist can synthesize across pathology, imaging, molecular, and clinical evidence and produce hypotheses that are biologically sound, demands new frameworks. We are seeking a Postdoctoral Researcher to build them. The Researcher will be embedded in the Machine Intelligence (MI) team at J&J Innovative Medicine, working in partnership with the c-brAIn academic network. The role begins with engagement in multi-modal neuroscience data – understanding what each modality reveals, how they relate, and where integration breaks down – and builds toward crafting the evaluation frameworks and standards by which agentic co-scientist systems are tested, validated, and trusted. The Researcher will work day-to-day with AI scientists in J&J’s Machine Intelligence group while partnering closely with translational and experimental teams across C-BRAIN’s academic network at Washington University in St. Louis and partner institutions. Mentorship is designed to build leaders at the Multi-Modal Data × AI Evaluation × Neurodegeneration interface, with opportunities for publications, cross-sector exposure, and leadership development.

KEY RESPSONSIBILITIES

Multi-Modal Data Integration Characterize and integrate biomedical data modalities – digital pathology (whole slide images), neuroimaging (PET, structural and functional MRI), omics (genomics, transcriptomics, proteomics, metabolomics), and longitudinal clinical data to develop specialized, domain-specific models for neurodegeneration Build and refine data engineering pipelines that harmonize heterogeneous modalities – reconciling differences in spatial resolution, temporal scale, and dimensionality – into unified analytical frameworks Identify where cross-modal integration produces genuine insight versus where it introduces noise or artifact, establishing ground truth for downstream AI evaluation Agentic AI Evaluation Critically assess AI-driven literature synthesis and automated “third reviewer” capabilities for detecting methodological weaknesses, logical gaps, and unsupported claims across data modalities Establish standards for how agentic systems incorporate overlooked or contradictory evidence such as negative findings, failed clinical trials, etc. and evaluate whether these integrations generate genuinely novel hypotheses Design evaluation frameworks for agentic AI systems operating across neuroscience data modalities – assessing whether models can reason credibly across imaging, omics, and clinical evidence Develop benchmarks using synthetic and real-world multi-modal datasets that probe AI co-scientist capabilities under realistic research conditions, testing for robustness, reproducibility, and alignment with expert-level biomedical reasoning Research & Communication Serve as a neurodegeneration domain expert within the AI/ML team, ensuring that model outputs remain anchored to clinically relevant disease questions Translate evaluation findings into actionable guidance for AI system development, bridging computational and experimental perspectives Publish evaluation methodologies and findings in leading journals and conferences (e.g., AD/PD, AAIC, NeurIPS) Articulate emerging AI/ML approaches – causal reasoning, intent classification, agentic planning – to diverse audiences with clear framing of practical applications in drug discovery Co-author manuscripts, concept papers, and translational strategy documents Required Qualifications PhD (or MD/PhD) in neuroscience, neurobiology, computational neuroscience, biomedical informatics, or a closely related field. (*Degree must have been completed within the last 3 years, or will be completed in the next 6 months.) Deep knowledge of neurodegenerative disease biology (Alzheimer’s, Parkinson’s, etc.) including disease mechanisms, experimental models, and translational challenges Hands‑on experience working with at least two of the following data modalities in a research context: neuroimaging (PET, MRI), digital pathology, omics, longitudinal clinical data Familiarity with large language model architectures and agentic AI frameworks (e.g., LangGraph, DSPy, or equivalent orchestration tools) Proficiency in Python and common ML/data engineering frameworks Excellent scientific communication skills and comfort working across computational, translational, and experimental teams Self‑directed, with the ability to work both independently and within a diverse, multi‑disciplinary team Preferred Qualifications Experience building data pipelines that integrate heterogeneous biomedical data types Familiarity with evaluation or benchmarking methodologies for AI/ML systems Experience with NLP techniques: named entity recognition, natural language inference, knowledge graph construction Knowledge of graph data structures, graph analytics, and graph platforms (Neo4j, Neptune) Familiarity with cloud infrastructure (AWS and/or Azure) for scalable pipelines Employees Are Eligible For The Following Time Off Benefits Vacation – up to 120 hours per calendar year Sick time - up to 40 hours per calendar year Holiday pay, including Floating Holidays – up to 13 days per calendar year of Work, Personal and Family Time - up to 40 hours per calendar year EEO Statement Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. Compensation & Benefits The anticipated base pay range for this position is $79,000 – $127,650. The Company maintains highly competitive, performance‑based compensation programs. Under current guidelines, this position is eligible for an annual performance bonus in accordance with the terms of the applicable plan. Bonuses are awarded at the Company’s discretion on an individual basis. Employees and/or eligible dependents may be eligible to participate in the following Company-sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long‑term disability, business accident insurance, and group legal insurance. Employees may be eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)). The compensation and benefits information set forth in this posting applies to candidates hired in the United States. Candidates hired outside the United States will be eligible for compensation and benefits in accordance with their local market. #J-18808-Ljbffr Johnson & Johnson Innovative Medicine