"Postdoctoral Fellow, Bioinformatics, Brain Tumor Drug Discovery and Development Program"

The Brain Tumor Drug Discovery and Development Program in the Department of Molecular and Medical Pharmacology at UCLA is seeking a highly motivated and skilled Postdoctoral Fellow/Research Scientist in Bioinformatics to lead bioinformatics-driven biomarker discovery and drug development efforts aimed at advancing precision therapies for brain tumors. The successful candidate will be instrumental in the design and execution of translational studies, will contribute to high-impact publications and grant submissions, and will have the opportunity to mentor junior researchers in computational and bioinformatics techniques. This position is supported by stable NIH, DOD, and philanthropy funding in collaboration with multi-disciplinary teams.

• Lead bioinformatics efforts to identify and validate biomarkers for brain tumors using high-throughput sequencing technologies.
• Develop, optimize, and manage bioinformatics pipelines for processing and analyzing large-scale sequencing data (e.g., whole exome sequencing, RNA sequencing, single-cell RNA sequencing).
• Collaborate with experimentalists and clinical researchers to design integrative computational analyses that inform experimental strategies and therapeutic interventions.
• Contribute to high-impact publications, present findings at conferences, and assist in the preparation of grant proposals.
• Mentor and guide junior bioinformatics researchers in the lab, promoting technical and career development.

Qualifications: The ideal candidate will have a Ph.D. in Bioinformatics, Computational Biology, or a related field, with a strong background in bioinformatics methods and data analysis. Previous experience with the following is highly desirable:

1. Data Processing: Proficiency in analyzing high-throughput sequencing data, including Whole Exome Sequencing, RNA sequencing, and single-cell RNA sequencing. Familiarity with the use of version control (Git) and virtual environments (e.g., conda, Docker) to manage and improve computational pipelines.
2. Data Storage and Management: Experience in managing large-scale -omics data, including data storage, organization, and inventory across multiple platforms. Strong skills in record-keeping, facilitating data upload to online repositories, and ensuring data integrity and reproducibility.
3. Data Analysis: Expertise in applying bioinformatics approaches to analyze complex datasets, including model fitting, statistical testing, and data visualization in R and/or Python. Ability to work closely with experimentalists to ensure analyses complement experimental goals and enhance data interpretation.
4. Advanced Computational Skills: Proficiency in bioinformatics tools and libraries (e.g., Bioconductor, STAR, DESeq2, Seurat) and familiarity with cloud computing platforms and scalable computing infrastructures for large datasets.

How to Apply: Interested candidates should submit a brief cover letter, curriculum vitae (CV), and contact information for at least two references.