Johnson & Johnson Innovative Medicine
Postdoctoral Scientist, In Silico Immune Disease Models (m/f/x)
Johnson & Johnson Innovative Medicine, Titusville, New Jersey, us, 08560
Job Overview
Johnson & Johnson Innovative Medicine is currently seeking a
Postdoctoral Scientist, In Silico Immune Disease Models
with a strong preference for location at one of our sites in Berlin, Germany; Beerse, Belgium; Spring House, PA; Cambridge, MA; Titusville, NJ; or La Jolla, CA. Remote work options within the US may be considered on a case-by-case basis and if approved by the company. Key Responsibilities
Lead collaborations with Translational Research, Discovery, and Development teams to develop AI/ML models that drive insights for personalized medicine. Analyze and integrate high-dimensional biological data from spatial transcriptomics and single-cell sequencing for model training and validation. Develop and implement scalable statistical and machine learning algorithms using large-scale transcriptomics datasets. Oversee the design of experiments that facilitate rigorous model evaluation in collaboration with cross-functional teams. Ensure compliance with internal coding standards, data integrity practices, and reproducibility protocols for research outputs. Communicate model performance and research findings effectively through technical reports, presentations, and contributions to peer-reviewed publications. Provide technical leadership and mentor junior researchers to enhance team capabilities and research output. Qualifications
A Ph.D. completed within the last three years in computer science, artificial intelligence, software engineering, or a related field. Proficiency in Python and C/C++. Experience designing and implementing reproducible workflows for large-scale transcriptomics data analysis. Strong background in developing and optimizing machine learning algorithms; knowledge graphs or ML-driven biological network modeling is strongly preferred. Experience applying algorithms in a biological context; molecular and immunological contexts are strongly preferred. Proven track record of impactful research with publications in top-tier peer-reviewed journals. Ability to define research strategies and set project milestones to drive innovation in foundational models. Strong communication skills to present complex concepts clearly to scientific peers and non-experts. Preferred Qualifications
Experience in oncology and/or immunology research. Knowledge of therapeutic strategies and clinical implications in cancer and immune-related diseases. Familiarity with multi-omics models and integrating data across multiple platforms. Note: This description preserves the core content related to the role and responsibilities while removing unrelated postings and extraneous internal notes.
#J-18808-Ljbffr
Johnson & Johnson Innovative Medicine is currently seeking a
Postdoctoral Scientist, In Silico Immune Disease Models
with a strong preference for location at one of our sites in Berlin, Germany; Beerse, Belgium; Spring House, PA; Cambridge, MA; Titusville, NJ; or La Jolla, CA. Remote work options within the US may be considered on a case-by-case basis and if approved by the company. Key Responsibilities
Lead collaborations with Translational Research, Discovery, and Development teams to develop AI/ML models that drive insights for personalized medicine. Analyze and integrate high-dimensional biological data from spatial transcriptomics and single-cell sequencing for model training and validation. Develop and implement scalable statistical and machine learning algorithms using large-scale transcriptomics datasets. Oversee the design of experiments that facilitate rigorous model evaluation in collaboration with cross-functional teams. Ensure compliance with internal coding standards, data integrity practices, and reproducibility protocols for research outputs. Communicate model performance and research findings effectively through technical reports, presentations, and contributions to peer-reviewed publications. Provide technical leadership and mentor junior researchers to enhance team capabilities and research output. Qualifications
A Ph.D. completed within the last three years in computer science, artificial intelligence, software engineering, or a related field. Proficiency in Python and C/C++. Experience designing and implementing reproducible workflows for large-scale transcriptomics data analysis. Strong background in developing and optimizing machine learning algorithms; knowledge graphs or ML-driven biological network modeling is strongly preferred. Experience applying algorithms in a biological context; molecular and immunological contexts are strongly preferred. Proven track record of impactful research with publications in top-tier peer-reviewed journals. Ability to define research strategies and set project milestones to drive innovation in foundational models. Strong communication skills to present complex concepts clearly to scientific peers and non-experts. Preferred Qualifications
Experience in oncology and/or immunology research. Knowledge of therapeutic strategies and clinical implications in cancer and immune-related diseases. Familiarity with multi-omics models and integrating data across multiple platforms. Note: This description preserves the core content related to the role and responsibilities while removing unrelated postings and extraneous internal notes.
#J-18808-Ljbffr