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.

Key Responsibilities:

* 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.

Ph.D. in Bioinformatics, Computational Biology, or a related field

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.

• 2-4 required (contact information only)

References may be contacted to verify experience.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.
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