Postdoctoral Scholar: Computational Immunology & Genomics

David Geffen School of Medicine at UCLA; Los Angeles (CA); Sur place; USD 55 000 - 65 000; Plein temps

Résumé du poste

The Division of Infectious Diseases at the David Geffen School of Medicine at UCLA seeks a full-time postdoctoral scholar in Computational Immunology and Genomics. The candidate will develop and apply computational, statistical, and machine-learning approaches to study human immune responses, host genetics, infectious disease, and vaccine immunity.

The role involves analyzing whole-genome sequencing, transcriptomics, single-cell RNA-seq, PhIP-Seq, immunophenotyping, and clinical data, with

Qualifications

• PhD or equivalent in bioinformatics, computational biology, genomics, biostatistics, data science, computer science, biomedical engineering, or related field.
• Experience with genomic and immunologic data analysis is preferred.

Responsabilités

• Develop and apply computational, statistical, and ML approaches to study immune responses, host genetics, infectious disease, and vaccine immunity.
• Analyze WGS, transcriptomics, single-cell RNA-seq, PhIP-Seq, immunophenotyping, and clinical data.
• Integrate multi-omics and clinical data to find biological signatures and mechanisms.
• Develop reproducible computational workflows for large genomic datasets.
• Collaborate with experimentalists and clinicians on study design, analysis, and manuscript preparation.

Connaissances

Computational biology

Bioinformatics

Genomics

Machine learning

Data science

Formation

PhD in Bioinformatics/Computational Biology/Genomics/Biostatistics/Data Science/CS/Bioengineering

Description du poste

The Division of Infectious Diseases at the David Geffen School of Medicine at UCLA seeks a full-time postdoctoral scholar in Computational Immunology and Genomics. The candidate will develop and apply computational, statistical, and machine-learning approaches to study human immune responses, host genetics, infectious disease, and vaccine immunity.

The role involves analyzing whole-genome sequencing, transcriptomics, single-cell RNA-seq, PhIP-Seq, immunophenotyping, and clinical data, with