Postdoctoral Scholar Interpretable AI Neuroscience Precision Medicine

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and Med Tech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.

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Post Doc – Data Analytics & Computational Sciences

Career Program

Cambridge, Massachusetts, United States of America, San Diego, California, United States of America

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Our Neuroscience team tackles the world’s toughest brain health challenges including multiple sclerosis, Alzheimer’s disease, Parkinson’s disease, myasthenia gravis, epilepsy, major depressive disorder, bipolar disorder, schizophrenia, and autism. This patient-focused team helps address some of the most complex diseases of our time.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

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Johnson & Johnson Innovative Medicine R&D is recruiting for a Postdoctoral Scholar, Interpretable AI – Neuroscience Precision Medicine
, a fixed-term position for 2 years, located in either Cambridge, MA or La Jolla, CA. This exceptional scientist will join the Computational Neuroimaging Technologies team within the Neuroscience Precision Measures organization. In this role, the individual will bring expertise in Interpretable AI and rule mining methodologies to advance our capabilities in patient-centered decision-making. The Scientist will collaborate closely with a cross‑functional team, analyzing clinical scale data alongside features from diverse domains, including molecular, digital, and imaging biomarkers.

By applying state‑of‑the‑art Interpretable AI methods, you will contribute to developing transparent, understandable models that support precision medicine strategies. These efforts will help ensure that regulators, payers, physicians and patients clearly understand the rationale behind treatment decisions while providing new insights into brain mechanisms underlying neurological diseases.

You will be part of a dynamic, interdisciplinary Precision Measures team with diverse expertise, driving value across our pipeline from discovery through development.

• Work within a team focused on linking clinical phenotype data to neural circuits and brain‑expressed targets.

• Develop and apply Interpretable AI methodologies to support discrete and continuous prediction problems, including treatment responsiveness, disease subtypes, and measures of brain circuit dysfunction.

• Leverage expertise in discrete optimization techniques and scalable computational approaches for rule mining to derive actionable insights.

• Establish and optimize Interpretable AI approaches for clinical trial data to enhance patient selection strategies for treatment response.

• Develop interpretable models that aid in biomarker discovery and validation, enhancing the understanding of disease mechanisms.

• Collaborate with cross‑functional teams, including clinicians, neuroscientists, and data scientists, to integrate multi‑modal data (molecular, digital, imaging) for comprehensive analysis.

• Stay current with the evolving landscape of Interpretable AI methodologies and their applications in neuroscience and precision medicine.

• Present findings to internal and external stakeholders, translating complex AI models into insights accessible to non‑technical audiences.

• Foster strong partnerships with the Data Science & Digital Health team, collaborating on cross‑functional projects to drive scientific innovation.

Required:

• PhD in Computer Science, Statistics, Applied…