Postdoctoral Position in Infectious Diseases - Herman Lab 2026-2027

University of California - Los Angeles (UCLA); Los Angeles (CA); On-site; USD 71,000 - 86,000; Full time

Job summary

University of California, Los Angeles (UCLA) is seeking a full-time postdoctoral scholar in Computational Immunology and Genomics within the Division of Infectious Diseases, Department of Medicine.

The role involves developing computational, statistical, and ML methods to study human immune responses, host genetics, infectious disease, and vaccine immunity in a collaborative lab setting in Los Angeles, California.

Qualifications

• PhD or equivalent doctoral degree in Bioinformatics, Computational Biology, Genomics, Biostatistics, Data Science, Computer Science, Biomedical Engineering, or a closely related quantitative field.
• Strong programming experience in Python and/or R.
• Experience analyzing high-dimensional biological or biomedical datasets.
• Experience with next-generation sequencing and computational genomics, transcriptomics, or related omics data.
• Strong foundation in statistics, including multivariate analysis and validation of quantitative models.
• Experience working in Linux/Unix-based computational environments.
• Ability to develop, troubleshoot, document, and maintain reproducible analyses.
• Ability to communicate computational results clearly to collaborators from diverse backgrounds.
• Strong scientific writing skills and demonstrated ability to contribute to peer-reviewed research.

Responsibilities

• Analyze whole-genome and next-generation sequencing data including QC, variant calling, and interpretation.
• Analyze single-cell RNA-seq data including QC, normalization, clustering, and differential expression.
• Analyze high-dimensional immunologic datasets such as systems serology and PhIP-Seq.
• Integrate genomic, transcriptomic, antibody, immunophenotyping, and clinical datasets.
• Develop and apply machine-learning and statistical models for classification and prediction.
• Collaborate with experimentalists on study design, analysis, and manuscript preparation.

Skills

Python/R programming

High-dimensional data analysis

Linux/Unix

Scientific writing

Education

PhD in Bioinformatics/Computational Biology/Genomics/Biostatistics/Data Science/CS/Biomedical Engineering

Tools

Nextflow

Snakemake

Git

Job description

Position Overview

Salary range: See Table 23. A reasonable estimate for this position is $71,491-$85,736.

Full-time postdoctoral scholar.

Position Description

The Division of Infectious Diseases in the Department of Medicine at the David Geffen School of Medicine at UCLA is seeking applicants for a full-time postdoctoral scholar position in Computational Immunology and Genomics. The successful candidate will develop and apply computational, statistical, and machine-learning approaches to investigate human immune responses, host genetics, infectious disease, and vaccine immunity. The position will work closely with experimental immunologists, clinicians, and computational researchers and will have opportunities to lead computational projects, develop new analytical approaches, contribute to manuscripts and grant applications, and generate first-author publications. Current projects in the laboratory integrate whole-genome sequencing (WGS), transcriptomics, single-cell RNA sequencing, antibody and systems-serology measurements, PhIP-Seq/epitope profiling, immunophenotyping, and clinical data. A major focus of the position will be identifying genomic and immunologic features associated with variation in immune responses and clinically relevant phenotypes. A Ph.D. or equivalent doctoral degree in Bioinformatics, Computational Biology, Genomics, Biostatistics, Data Science, Computer Science, Biomedical Engineering, or a closely related quantitative field is required.

Research activities may include analysis of whole-genome and next-generation sequencing data (including quality control, variant calling, annotation, filtering, genetic association, and biological interpretation), analysis of single-cell RNA-seq data (including quality control, normalization, dimensionality reduction, clustering, cell-type annotation, differential expression, pathway analysis, and comparison of cellular states across clinical or experimental groups), and analysis of high-dimensional immunologic datasets (including systems serology, antibody profiling, PhIP-Seq, flow-cytometry-derived measurements, and related immune assays).

Research activities may also include integration of genomic, transcriptomic, antibody, immunophenotyping, and clinical datasets to identify biological signatures and mechanisms associated with immune phenotypes, as well as development and application of machine-learning and statistical models for classification, prediction, feature selection, dimensionality reduction, biomarker discovery, and multimodal data integration.

Related research efforts may also include evaluation and implementation of emerging computational and machine-learning methods when scientifically appropriate, development of reproducible computational workflows for processing and analyzing large genomic and immunologic datasets, visualization and communication of complex results to both computational and experimental collaborators, and collaboration with laboratory investigators on experimental design, statistical analysis, interpretation of results, manuscript preparation, and grant applications.

The candidate will be encouraged to develop an independent research direction within the broader scientific interests of the laboratory and to contribute to the development of new computational approaches for systems immunology, human genetics, infectious disease, and vaccinology.

The shared values of the DGSOM are expressed in the Cultural North Star, which was developed by members of our community and affirms our unswerving commitment to doing what's right, making things better, and being kind. These are the standards to which we hold ourselves, and one another. Please read more about this important DGSOM program at Cultural North Star.

Basic qualifications

• A Ph.D. or equivalent doctoral degree in Bioinformatics, Computational Biology, Genomics, Biostatistics, Data Science, Computer Science, Biomedical Engineering, or a closely related quantitative field is required.

Additional qualifications

• The candidate must have strong programming experience in Python and/or R.
• The candidate must have experience analyzing high-dimensional biological or biomedical datasets.
• The candidate must have experience with next-generation sequencing and computational genomics, transcriptomics, or related omics data.
• The candidate must have strong foundation in statistics, including multivariate statistical analysis and appropriate validation of quantitative models.
• The candidate must have experience working in Linux or Unix-based computational environments.
• The candidate must have ability to independently develop, troubleshoot, document, and maintain reproducible computational analyses.
• The candidate must have ability to communicate computational results clearly to collaborators with diverse scientific backgrounds.
• The candidate must have strong scientific writing skills and demonstrated ability to contribute to peer-reviewed research.

Preferred qualifications

• Experience in one or more of the following areas is preferred: whole-genome sequencing and human genetic variation, germline variant calling/annotation/rare-variant analysis/genetic association studies, single-cell RNA-seq/other single-cell omics, machine learning applied to biomedical data, multimodal or multi-omics data integration, high-dimensional immunology datasets, development of reproducible bioinformatics pipelines using workflow-management and containerization tools, or high-performance or cloud computing for large genomic datasets.
• Experience with single-cell RNA-seq analysis using commonly used computational frameworks such as Seurat, Scanpy, or related approaches is preferred.
• Experience developing or applying machine-learning approaches including regularized regression, random forests, gradient-boosting methods, PLS-based approaches, neural networks, or related methods is preferred.
• Experience with feature selection, model interpretation, cross-validation, external validation, and methods for avoiding overfitting in high-dimensional biomedical datasets is preferred.
• Experience integrating genomic information with transcriptomic, immunologic, or clinical phenotypes is preferred.
• Familiarity with HLA/immunogenomics, antibody profiling, systems serology, PhIP-Seq, B-cell biology, infectious disease, or vaccine immunology is preferred.
• Experience with workflow tools such as Nextflow or Snakemake, version control such as Git, and reproducible computational environments is preferred.
• Familiarity with GPU-accelerated genomics, high-performance computing, or cloud-based analysis of large sequencing datasets is preferred.
• Interest in learning systems immunology and working closely with experimental scientists on clinically focused basic and translational research is preferred.

Document Requirements

• Curriculum Vitae - Your most recently updated C.V.
• Cover Letter
• Statement of Research
• UCLA Mission Statement - As the nation's premier public research university, UC's mission is the creation, dissemination, preservation and application of knowledge for the betterment of our global society. We have a particular responsibility to the people of California which we express in the excellence of the education we provide, the impact of the research we do, the comprehensive, life-saving medical services we provide, and the public service mission we are devoted to. The University of California promotes the social mobility of its students, equips them with the tools and experience that furthers their ambitions, and regards their accomplishments across the life span as evidence of the profoundly positive impact of higher education. Deepen our engagement with Los Angeles Expand our reach as a global university Enhance our research and creative activities Elevate how we teach Become a more effective institution Prompt for candidates for recruitment: Reflecting on your personal and professional experiences, highlight your past contributions and future commitments to advancing UCLA's mission as embodied in the 2023-28 strategic plan. These accomplishments and ambitions may be discussed in the context of describing your teaching, scholarship, and service.

Reference Requirements

• 3 required (contact information only)

Provide contact information of 3 professional references.

Location

Los Angeles, CA

About UCLA

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.

• "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.
• UC Sexual Violence and Sexual Harassment Policy
• UC Anti-Discrimination Policy for Employees, Students and Third Parties
• APM - 035: Affirmatve Action and Nondiscrimination in Employment