Omics Data Science for Immuno-Engineering - Research Professor

Oklahoma Center of ImmunoEngineering; Norman (OK); Vor Ort; USD 80.000 - 110.000; Vollzeit

Zusammenfassung

The University of Oklahoma invites applications for a non-tenure track Research Assistant Professor position in Omics Data Science and Bioinformatics for Immuno-Engineering. This research-focused role will support interdisciplinary multi-omics research through collaborative data analysis and methodology development for immuno-engineering applications.

The successful candidate will join interdisciplinary teams, develop computational workflows for large-scale omics data, and contribute to grant

Qualifikationen

• Applicants must have a Ph.D. in Computer Science, Bioinformatics, Computational Biology, Data Science, Biomedical Informatics, Statistics, or a closely related field. Candidates should have experience in computational analysis of biological or biomedical data, strong programming skills, experience with scalable computing environments, and the ability to work effectively in interdisciplinary teams.

Aufgaben

• Collaborate with investigators on the design and analysis of multi-omics studies.
• Develop, validate, and apply computational workflows for large-scale omics data, including single-cell and spatial data.
• Support data integration, interpretation, manuscript preparation, and data sharing.
• Lead research and development of new bioinformatics, machine learning, and data science methods for immuno-engineering.
• Develop grant applications and contribute to proposals in immuno-engineering.
• Participate in workshops, consultations, and other collaborative research activities.

Jobbeschreibung

The University of Oklahoma invites applications for a non-tenure track Research Assistant Professor position in Omics Data Science and Bioinformatics for Immuno-Engineering. This research-focused role will support interdisciplinary multi-omics research through collaborative data analysis and methodology development for immuno-engineering applications.

The successful candidate will join interdisciplinary teams, develop computational workflows for large-scale omics data, and contribute to grant