Janssen Research & Development is hiring for an Associate Director, Genetic Informatics for our World Without Disease Accelerator (WWDA) and Lung Cancer Initiatives (LCI) Team. The position is based in Cambridge, MA with flexibility to also be based in Horsham, PA or Fort Washington, PA.
We seek a talented, collaborative inter-disciplinary scientist to empower data-driven decisions by ways of utilizing integrative genetics and genomics for early detection, interception and prevention of diseases. This individual will play a key scientific role leveraging innovative computational analyses to translate insights from large public and private cohorts that include collections of genetics, EHR, single-cell and molecular profiling data.
Johnson & Johnson is one of the few global healthcare organizations with a history of leadership in the device, pharmaceutical and consumer healthcare sectors. Here at World Without Disease Accelerator (WWDA) & the Lung Cancer Initiatives (LCI) within Johnson & Johnson, we believe that the convergence of the capabilities above will eventually allow providers to detect and intercept disease before the earliest clinical symptoms manifest. We are looking for candidates who share this view and are passionate about leveraging statistical genetics with multi-view molecular profiling including single-cell and bulk omics.
Successful candidate will work alongside his/her scientific peers to design data analysis strategies, interpret results and drive decision-making in the pursuit of prevention, interception, and the cure of disease. He/she will have experience working in interdisciplinary teams and gaining support for the use complex analytics to answer biological questions. As a member of the global Data Sciences and Predictive Biomarkers team, you will join a collaborative, international team of scientists and proactively contribute your experience and expertise to achieving the WWDA/LCI vision.
Strong interest in the inter-disciplinary application of computational analysis methods to life sciences data is imperative, as is rich background and expertise in statistical genetics, GWAS fine-mapping, polygenic risk scores, and interpretation of causality. Hands-on expertise in single-cell analyses is a prerequisite. In addition to being the lead informatician, successful candidates are expected to be a thought leader in identifying relevant data resources, and drive subsequent access management, harmonization, and integration to inform drug discovery and development efforts.
Working in collaboration with computational, biological and clinical scientists across the J&J organization, responsibilities include but are not limited to:
Scientific leadership including hands-on analyses to oversee human genetics cohort studies for risk stratification to facilitate early disease detection.
Scientific leadership including hands-on analyses to oversee mechanistic single-cell RNAseq studies.
Scientific report writing and presentation of methods, results and conclusions to a publishable standard.
Contribution to planning and execution of collaborative projects with leading academic and commercial research groups worldwide.
Johnson & Johnson is an Affirmative Action and 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, or protected veteran status and will not be discriminated against on the basis of disability.
- A Ph.D. in genetics, computational biology, bioinformatics, or related field from a recognized higher-education establishment.
- 7+ years post-doctoral experience of inter-disciplinary computational and genetics research in university, hospital or biotechnology environments.
- Deep expertise in statistical genetics including GWAS, QTL, polygenic risk scores, Mendelian Randomization, and fine-mapping loci using omics.
- Deep knowledge in single-cell RNAseq analyses.
- Previous experience of research supervision and track record of peer-reviewed publication in relevant scientific journals.
- Expertise in algorithmic implementation, statistical programming and data manipulation, using e.g. R/Bioconductor, Python, and contemporary, open-source bioinformatics tools and database structures.
- Proven problem-solving skills, collaborative nature and adaptability across disciplines.
- Excellent verbal and written communication skills. Fluent verbal and written English language skills prerequisite.
- Previous participation in consortia studies a plus.
- Experience in integration of single-cell and bulk omics highly desirable.
- Domain knowledge in one or more of the following therapeutic areas: Type 1 Diabetes, Lung Cancer, or Pediatrics allergies