The Manager, Bioinformatician, will lead data science and computational research operations within a multidisciplinary research environment at the intersection of biomedical science, systems biology, and translational health care research. This position requires deep expertise in multimodal biomedical data integration and advanced quantitative and computational approaches for analyzing large-scale biological data. The Mgr, Bioinformatician will oversee complex research projects, ensure rigor and reproducibility of data pipelines, collaborate with external foundations and industry partners for data analysis, and provide mentorship and leadership to a team of bioinformaticians, data scientists, and trainees.

This position is designed to recognize and formalize advanced contributions beyond senior bioinformatics responsibilities, with an emphasis on research program leadership, cross-disciplinary collaboration, and data stewardship for high-impact publications, grants, and translational partnerships.

Responsibilities

• Data & Research Leadership
  • Direct design, implementation, and maintenance of computational pipelines for large-scale biological and multi-omic data.
  • Lead the application of advanced statistical, computational, and machine learning approaches to analyze complex biological systems.
  • Manage integration of multi-modal data types (e.g., genomic, metabolomic, transcriptomic, and clinical datasets) using appropriate quantitative methods..
  • Oversee quality control, reproducibility, and compliance with institutional and federal data management standards.
  • Support and advise principal investigators, collaborators, and external partners to conceptualize new projects, write grants, and publish findings in high-impact journals.
• Management & Supervision
  • Provide day-to-day management of bioinformatics and data analysis staff, including task assignment, workflow prioritization, and performance review.
  • Mentor PhD students, postdoctoral researchers, and junior staff in advanced computational methods and best practices.
  • Foster a collaborative team culture that bridges computational and experimental scientists.
• Strategic & Translational Impact
  • Ensure data pipelines and models are adaptable for clinical and translational applications across a range of health-related research areas.
  • Drive innovation in computational methods, including scalable data processing, and advanced analytical frameworks..
  • Contribute to intellectual property development, external collaborations, and industry partnerships where relevant.

REQUIRED QUALIFICATIONS:

• PhD in Computational Biology, Bioinformatics, Statistics, Computer Science, or a related field.
• 5+ years of postdoctoral or equivalent research experience with a strong publication record in computational biology quantitative sciences or related disciplines.
• Demonstrated leadership experience in managing teams or projects in an academic, clinical, or research environment.
• Expertise instatistical and computational methods for analyzing complex biological data
• Demonstrated ability to select and apply appropriate analytical approaches to diverse research questions
• Advanced experience in large-scale biological data analysis and high-throughput sequencing data.
• Proficiency with machine learning for multi-modal biomedical datasets (e.g., Python, R, ML/AI frameworks).
• Strong project management and organizational skills with ability to manage multiple projects simultaneously.
• Proven ability to mentor and lead technical staff and trainees.
• Excellent communication and collaborative skills to work across computational, experimental, and clinical teams.

PREFERRED QUALIFICATIONS:

• Experience with Advanced modeling approaches (e.g. Bayesian methods, dynamical systems models, or network-based analytical frameworks)
• Familiarity with translational research and regulatory requirements for health care data.
• Prior experience securing grants or contributing to successful funding applications.

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