Janssen Research & Development is a world-class biotech and pharmaceutical organization committed to research and development of innovative therapies for diseases of great need.  Janssen Immunology Research & Development focuses on improving the health and lifestyles of people with serious immunological and inflammatory conditions worldwide, and today has a leading portfolio of medicines to treat psoriasis, Crohn’s disease, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis, atopic dermatitis and ulcerative colitis. Janssen Immunology recognizes data science plays an increasingly important role in drug discovery and development, from target validation to improved patient selection and robust, predictive molecular, imaging and digital end points.  As such, Janssen Immunology is committed to building out a foundational new data science capability, harnessing novel developments in analytical technologies and processes, to power its portfolio and pipeline as well as enhance its ability to survey the external landscape for productive partnerships.

POSITION COMPONENTS

In this role, you will work alongside the Data Engineering and Platforms team, a part of Immunology Data Science department.  You will closely partner with scientists and postdocs from Immunology Discovery and Immunology Biomarkers, as well as with external academic collaborators, to develop computational methodology and frameworks for rational design of combination therapies for inflammatory and autoimmune diseases. The project will also involve the integration of large, high-quality, multiscale, clinical, in vitro and in vivo datasets available to Janssen, with new data generated by lab-based scientists, leading to hypotheses for pre-clinical validation and clinical consideration.  

To benefit from the complementary knowledge captured in each dataset, you will use the state-of-the-art machine learning approaches to develop methodologies for extracting and visualizing relationships between different data types.  The hypotheses generated though your efforts will be translated into further in vitro or in vivo experiments, leading to additional datasets to be used for model validation and improvement.

KEY RESPONSIBILITIES

• Develop and implement computational frameworks for integrating multiscale data from clinical trials with data from treatments of human and murine in vitro and in vivo systems
• Identify, retrieve and process data from internal and external sources as needed to achieve project goals
• Analyze human and murine high content (omic) data sets and integrate them with other available data
• In collaboration with lab-based scientists, propose prioritizations of targets and combinations for treatment of inflammatory and auto-immune diseases; propose experiments for validation of derived hypotheses
• Develop approaches for effective visualization and presentation of experimental results and computational predictions to wide audiences
• Publish findings in peer-reviewed journals

QUALIFICATIONS

• PhD degree in Computer Science, Applied Mathematics, Physics, Mathematics, Engineering, Statistics, Bioinformatics or Computational Biology is required
• Proven track record of scientific productivity reflected through publications in peer-reviewed scientific journals is required
• Strong oral and written communication skills are required
• Demonstrated ability to work in diverse, interdisciplinary teams is required
• Proficiency in a general-purpose programming language such as Python, C, C++, Java, Scala, Go or similar is required; Python is preferred
• Experience in designing and implementing scientific algorithms, workflows or applications is required
• Experience with numerical computation, network analysis, machine learning, neural networks, Bayesian approaches, information theory, non-negative matrix factorization or dimensionality reduction is preferred
• Experience with high-performance and cloud computing environments is preferred
• Familiarity with basics of biology or medicine is preferred
• Experience with processing and analyzing omics (transcriptomics, proteomics, genotypes etc.) or other high-dimensional data is preferred

  We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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