Responsibilities:

• Apply advanced statistics and machine learning technologies to support the identification of novel therapeutic targets, target validation, disease selection/expansion, and identification of translational biomarkers.
• Design and implement machine learning models to analyze large-scale genomic datasets from human disease studies.
• Utilize experience in single cell and spatial transcriptomics data analysis to derive deeper biological insights.
• Apply knowledge of biological pathways, data visualization, network, and systems biology to enhance understanding (experience in these areas is a plus).
• Interpret and present analysis results clearly and concisely to colleagues and collaborators.
• Develop and apply innovative analysis approaches when standard methods are inadequate.
• Maintain high standards of data integrity and ethics throughout the research process.
• Stay updated with the latest advancements in the field through regular review of scientific literature and participation in online courses/conferences.

Qualifications:

• Strong scientific understanding and hands-on experience in statistical and machine learning approaches as applied to bioinformatics.
• Proficiency in programming languages such as Python and R.
• Understanding of biology is preferred.
• Excellent written and verbal communication skills.

Education:

• Ph.D. or Master’s degree in a related scientific discipline (Computer Science, Genomics, Biostatistics, or Bioinformatics).

1st Shift

Year Contract

Up to 43 per hr