Postdoctoral Position in Infectious Diseases - Herman Lab

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.

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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.