Postdoctoral Scientist, Human Omics of Preclinical Safety Prediction, AI/ML

• Job title Postdoctoral Scientist, Human Omics of Preclinical Safety Prediction, AI/ML
• Function Career Programs
• Sub function Post Doc - Drug Discovery & Pre-Clinical/Clinical Development
• Category Post Doc - Drug Discovery & Pre-Clinical/Clinical Development (ST5)
• Location Spring House / United States of America
• Date posted May 20 2025
• Requisition number R-012723
• Work pattern Hybrid Work

This job posting is anticipated to close on May 27 2025. We may however extend this time period, in which case the posting will remain available on www.careers.jnj.com to accept additional applications.

Description

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 MedTech, 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. Learn more at

Job Function:

Career Programs

Job Sub Function:

Post Doc - Drug Discovery & Pre-Clinical/Clinical Development

Job Category:

Career Program

All Job Posting Locations:

Spring House, Pennsylvania, United States of America

Job Description:

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.

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

We are seeking an exceptional Postdoctoral Scholar passionate about genetics and multiomics, complex traits, and data sciences. This role focuses on enhancing target risk prediction through validation studies, off-target risk estimation, and cross-species evolutionary metrics. We are looking for our Postdoctoral Scholar to be located in Springhouse, PA.

Purpose:

Our expertise in Janssen R&D 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. You will join the Janssen's Preclinical Sciences and Translational Safety (PSTS) organization and work closely with the Population Analytics & Insights (PAI) team in Data Sciences & Digital Health (DSDH). The PAI team combines the power of 'omics data with AI to generate scalable, cutting-edge solutions and insights in drug development. Collaborating with the PSTS, we integrate omics data to improve preclinical safety profiling and help standardize safety evaluation in early drug development.

You will be responsible for:

• Optimize, and validate state-of-the-art models to extract translational and actionable insights from 'omics and cheminformatic data

• Design and implement validation protocols to evaluate (preclinical) safety predictions

• Integrate cross-species conservation and phenotype concordance metrics to enhance prediction.

• Clearly articulate complex technical methods, biological information, and results to diverse audiences, including scientists, stakeholders, and decision-makers to facilitate informed decision-making and drive project success

• Author scientific publication in top-tier journals and conferences

Required qualifications:

• PhD in genetics, population genetics, computational biology, epidemiology, biomedical sciences, toxicology, statistics, data sciences, or related field completed within the past 3 years or to be completed in the upcoming 6 months.

• Strong experience in driving research in human, animal, or evolutionary genetics and genetic associations with complex traits/disease.

• In depth understanding of omics-related data including genetic sequencing, bulk and single-cell expression, proteomics, as well as related analysis including GWAS, PheWAS, TWAS, etc.

• Proficiency in programming languages such as Python, R, and/or C++.

• Proficiency in statistical analysis and data handling, data cleaning, normalization of large-scale datasets.

• Proven scientific excellence as evidenced by publications, patents, and/or high-level presentations.

• Ability to effectively communicate complex technical concepts and results to a wide range of audiences, including non-technical stakeholders.

• Demonstrated experience working on interdisciplinary teams.

• Self-motivated and capable of driving projects forward independently with minimal daily oversight.

Preferred qualifications:

• Understanding and experience with drug compounds or cheminformatics.

• Familiarity with machine learning techniques such as supervised learning, self-interpretable multiple instance learning, ML algorithms such as random forest, SVM, boosting, neural networks, and optimization methods.

• Familiarity of evolutionary genetics including phylogenetics, gene similarity metrics, and gene constraint metrics.

• Familiarity and experience handling health coding systems such ICD, OMOP, and/or MedDRA.

• Familiarity and understanding of early drug development safety evaluation.

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.

Johnson and Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, please email the Employee Health Support Center (...) or contact AskGS to be directed to your accommodation resource.