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                ) the information in your candidate profile as it will transfer to your application. Job Title: Faculty - Department of Biomedical Informatics, Division of Bioinformatics and Computational Biology (Open rank/Tenure 
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                Variant Annotation Scientist will perform genomic variant annotation and bioinformatics analysis for clinical testing. Primary responsibilities will include the development and use of bioinformatics 
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                goal of Dr. Kes lab is to develop computational approaches and leveraging bioinformatics tools, metagenomic sequencing, multi-omics data, machine learning, and wet-lab techniques to investigate the role 
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                repair. Perform bioinformatics analyses of genomic, transcriptomic, and proteomic datasets to support experimental findings and generate new hypotheses. Collaborate with team members to design, execute 
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                % Performing research (protein characterization, bioinformatics) 20% Contributing to reports, manuscripts, project reporting, and grant proposals We are seeking a highly motivated Research Scientist with 
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                % Performing research (protein characterization, bioinformatics) 20% Contributing to reports, manuscripts, project reporting, and grant proposals We are seeking a highly motivated Research Scientist with 
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                , and seminars; supervise Graduate and Undergraduate students in the laboratory. Experience and Qualifications Required and/or Desired PhD or equivalent degree required; experience in bioinformatic data 
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                bioinformatics tools. Proficiency in R, Python, and data visualization platforms. Prior experience in cardiovascular or vascular biology research. Create a Job Match for Similar Jobs Logo About The Ohio State 
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                clinical, bioinformatics, and industry partners to integrate laboratory findings into translational and clinical projects. Leveraging a clinical oncology background to ensure translational relevance and 
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                . The overarching goal of Dr. Ke’s lab is to develop computational approaches and leveraging bioinformatics tools, metagenomic sequencing, multi-omics data, machine learning, and wet-lab techniques to investigate