Post Doc, R&D Immunology - Population Analytics & Insights

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 jnj.com

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Job Function:

Career Programs

Job Sub Function:

Post Doc – R&D Product Development

Job Category:

Career Program

All Job Posting Locations:

Spring House, Pennsylvania, United States of America

Job Description:

About Innovative Medicine

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 https://www.jnj.com/innovative-medicine

Johnson and Johnson Innovative Medicine (JJIM) is recruiting a Postdoctoral Scholar to work within the group (Data Sciences organization) on drug target identification and evaluation to support alignment of priorities with the Immunology therapeutic area.

The primary location for this position is Spring House, PA

The Data Science Analytics & Insights organization develops innovative solutions using a variety of data sources across multiple different disease\areas. We are looking for a highly motivated and self-driven individual who will creatively analyze large-scale clinical, genetic, omics and cell phenotype data to advance our drug discovery pipeline in R&D.

At J&J, we strive to bring in the brightest minds in pursuit of developing effective and safe therapeutics for patients around the globe.

Role & responsibilities:

• Construct an analytic framework by integrating perturbation, ontology and cellular phenotyping with molecular based datasets including genomics, transcriptomics, proteomics, to further enhance target evaluation, and patient stratification.
• Use multiple inference and ML methods linking molecular targets to disease states/characteristics, to associate targets with disease pathways, and to validate predicted mechanisms systematic on-/off-target toxicity predictions. These approaches require innovative computational methods such as network-based models, machine learning, and novel algorithmic approaches to mining biological data.
• Provide scientific technical expertise in modeling multimodal data (including genetic, transcriptomics, proteomic and functional data) to predict target pathway activity and synergistic effects.
• Apply or develop a wide variety of statistical modeling and AI/ML methods to analyze phenomic, multiomic and biobank level data to identify targets associated therapeutic with clinical and/or molecular segments and biomarkers associated with immune mediated diseases.
• Provide design and analysis consultation for questions of interest to our Immunology colleagues and facilitate interactions between colleagues across the organization.
• Translate findings from computational analyses to support functional, biological and pharmacological validation.

Job Qualifications:

Required skills

• A Ph.D. in a quantitative field with a strong biological basis – Bioinformatics, Computational Biology, Systems Biology, Statistical Genetics, or related fields.
• Completed PhD program.
• Experience with multi-omic data (RNA gene expression, proteomics, epigenomics, genetics) at both bulk and single cell level.
• Working knowledge of databases and analytic approaches associated with gene/pathway ontology, such as network analysis.
• Proficient in programming and computational skills and demonstrated ability to work with a group of scientists to deliver on objectives in defined timelines.
• Independent, self-motivated, innovative, and able to excel in a goal-oriented, multifaceted and fast-moving team environment.
• Outstanding communication, organizational and leadership skills, with a successful track record of publication and collaboration with cross-functional scientific teams.

Preferred skills

• Experience working with Immunology projects.
• Expertise in perturbation data and analysis.
• Experience with advanced analytical approaches (NLP, ML/AI, LLM) to extracting relevant sources of annotation of cellular states, functions and localization from unstructured data.
• Experience with predictive models associated with evaluation of target engagement and druggability.

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