Principal Scientist, Biological Network Analytics

Johnson & Johnson Innovative Medicine • Spring House, PA

6d • Onsite

About The Position

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. As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Discovery & Pre-Clinical/Clinical Development Job Sub Function: Biological Research Job Category: Scientific/Technology 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 We are searching for the best talent for a Principal Scientist, Biological Network Analytics to be located in Spring House, PA. Purpose: This role will directly support the broader Multiomic Discovery efforts through integration and analysis of multiple high dimensional biology datasets within the Biological Network Analytics group and contribute to the understanding of complex biology through advanced data analysis methods.

Requirements

• PhD in Cell Biology, Molecular Biology, Computational Biology, Bioinformatics or related discipline required
• A minimum of 6 years biotech of pharmaceutical industry experience is required
• Strong communication and presentation skills is required
• Proficiency in programming languages such as R or Python is required
• Knowledge of machine learning algorithms, statistical modeling, and unsupervised analysis techniques are required
• Experience with Multiomic Datasets is required
• Demonstrated ability to work across disciplines and functional areas is required
• Ability to apply novel approaches to address complex biology questions, as evidenced through strong peer-reviewed publications is required
• Excellent written communication, verbal communication, and oral presentation skills are required

Nice To Haves

• Post-doc fellowship in related field preferred
• Experience as a problem solver, and team collaborator able to facilitate understanding between biologists and data scientists is preferred
• Ability to manage multiple projects and meet deadlines is preferred
• Knowledge of statistical methods for biological data analysis is preferred
• Knowledge of cellular assay development and applications in drug discovery is preferred
• Experience working with and/or guiding external collaborators in industry or academia is preferred
• Strong background in statistical analysis and data visualization techniques is preferred

Responsibilities

• designing, implementing and validating computational models to study biological processes
• analyzing and integrating large datasets generated from multiple platforms including NGS, Proteomics, and high content imaging
• applying large scale Multiomic capabilities to support a modality agnostic portfolio across therapeutic areas
• partnering with wet and dry lab stakeholders within and Multiomic Discovery
• collaborating with cross-functional teams to support the design and implementation of experiments as part of broader Multiomic & High Dimensional Biology endpoints
• partnering with Therapeutic Area, Data Sciences, Safety, and In Silico Design teams to provide unbiased screening results supporting modality and indication agnostic drug discovery

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree