Assistant Professor – Computational Biology and Bioinformatics (Tenure Track)

position in Computational Biology and Bioinformatics. We seek a highly collaborative computational scientist with broad expertise in the analysis and interpretation of genomic, epigenomic, single-cell, spatial, and multiomic data. The successful candidate will join an interdisciplinary genomics research environment and work closely with investigators across the Center and throughout the university. This is primarily a collaborative faculty position designed to provide computational genomics and bioinformatics expertise for multiple research projects supported by the Center. Responsibilities: The successful candidate will: Lead and perform bioinformatics and computational analyses across diverse genomic and multiomic platforms, including whole-genome sequencing (WGS), DNA methylation sequencing (WGBS/RRBS), single-nucleus DNA methylation sequencing (snDNAm-seq), RNA-seq, ATAC-seq, single-cell/single-nucleus RNA-seq, single-cell chromatin and multiome data, and spatial transcriptomics/genomics. Analyze emerging multimodal sequencing data, including biomodal duet multiomics/six-letter sequencing integrating genomic sequence with 5mC and 5hmC information. Develop and maintain reproducible computational pipelines and apply appropriate statistical and computational approaches for data integration, interpretation, visualization, and biological discovery. Collaborate with investigators and research teams across campus to develop analytical strategies, interpret results, and address biological and biomedical questions. Contribute to scientific manuscripts, presentations, progress reports, and grant applications, including preparation of publication-quality figures, tables, and data summaries. Present analytical results and communicate computational findings effectively to investigators and collaborators. Provide bioinformatics guidance and mentorship to postdoctoral fellows, graduate students, research staff, and collaborating investigators. Help maintain the Center's bioinformatics computing infrastructure and servers, including bioinformatics software, analytical environments, databases, and computational pipelines, and assistant with the management and backup of large genomic datasets. Evaluate and implement emerging computational approaches, including artificial intelligence (AI), machine learning, large language models (LLMs), and AI-assisted genomic data analysis. Qualifications: Applicants should have: A PhD or equivalent doctoral degree in Bioinformatics, Computational Biology, Genomics, Computer Science, Biostatistics, or a closely related field. Postdoctoral or equivalent research experience in computational genomics or bioinformatics. Demonstrated hands-on experience analyzing multiple types of high-throughput sequencing and genomic data. Strong proficiency in R and Python, Linux-based computing, and high-performance computing environments. Strong knowledge of statistical and computational methods for genomic and multiomic data analysis. A strong publication record demonstrating significant contributions to genomics, bioinformatics, or computational biology research. Excellent communication skills and demonstrated ability to work effectively in multidisciplinary and collaborative research teams. A strong interest in a collaborative faculty career supporting multiple research programs. Expertise in single-cell and spatial omics, DNA methylation/epigenomics, integrative multiomics, workflow development, AI/machine learning, and large language models (LLMs) is highly desirable. Position Environment The Center for Genomics provides advanced genomic technologies, computational infrastructure, and a highly collaborative research environment supporting investigators and research programs across Loma Linda University. Salary and compensation: Competitive salary starting at $91,000 per year, commensurate with experience, with a comprehensive benefits package. Application Applicants should submit to Charles Wang ( chwang@llu.edu ) a curriculum vitae, a cover letter describing their computational genomics expertise and experience working in collaborative research environments, and contact information for three references. Applicants are encouraged to describe their specific contributions to genomic data analysis in representative publications.