Postdoc Bioinformatics Lead: Multi-Omics for Malaria

Liverpool School of Tropical Medicine; Liverpool; On-site; GBP 34,000 - 48,000; Full time

Benefits offered by this job

Career development

Wellbeing support

30 days leave

Pension schemes

Cycle to work

Sports centre access

Family policies

Job summary

Liverpool School of Tropical Medicine is seeking an experienced Post Doctoral Research Associate to lead computational analyses of multi-omics data in resistance to malaria vectors. You will work within the Chemical Biology Group, Department of Vector Biology, to integrate transcriptomic, proteomic, genomic, and phenotypic data with insecticide uptake and metabolism studies.

You will develop reproducible Python/R workflows, apply statistical and interpretable machine-learning approaches, and

Qualifications

• PhD in bioinformatics, computational biology, genomics, proteomics, or related field with substantial computational experience.
• Strong experience analysing high-dimensional molecular data across omics types.
• Proficiency in Python and/or R with maintainable computational workflows.

Responsibilities

• Lead transcriptomic and proteomic analyses from QC to differential expression and enrichment.
• Integrate multi-omics data with phenotypic and uptake/metabolism evidence.
• Develop and apply ML approaches for multi-omics integration and resistance phenotype prediction.
• Design and interpret functional validation studies, including RNAi where appropriate.
• Contribute to reproducible workflows and data provenance across the team.

Skills

Bioinformatics

Computational biology

Genomics

Biostatistics

Data science

Python

R

Machine learning

Education

PhD in bioinformatics, computational biology, genomics, proteomics, systems biology, biological sciences, computer science, or closely related

Tools

Python

R

Linux/command-line

Job description

Liverpool School of Tropical Medicine is seeking an experienced Post Doctoral Research Associate to lead computational analyses of multi-omics data in resistance to malaria vectors. You will work within the Chemical Biology Group, Department of Vector Biology, to integrate transcriptomic, proteomic, genomic, and phenotypic data with insecticide uptake and metabolism studies.

You will develop reproducible Python/R workflows, apply statistical and interpretable machine-learning approaches, and