Job Overview

We are seeking a Research Fellow to contribute to research involving quantitative microbial analysis using multi-omics approaches. The successful candidate will support laboratory and computational research activities, including microbial cultivation, multi-omics data generation and analysis, bioinformatics, and modelling of microbial systems.

The role offers opportunities to work in a multidisciplinary research environment and contribute to projects in microbiology, systems biology, microbial ecology, and related fields.

Key Responsibilities

• Conduct quantitative microbial research using genomic, transcriptomic, fluxomic, and other multi-omics methodologies.
• Perform molecular microbiology experiments, including microbial cultivation, sample processing, and laboratory analyses.
• Analyse and interpret biological datasets using computational and bioinformatics tools.
• Develop and apply metabolic, ecological, statistical, or related models to address research objectives.
• Support the operation and optimisation of microbial culture systems, including bioreactors and defined culture platforms where applicable.
• Prepare research reports, scientific manuscripts, presentations, and project documentation.
• Collaborate with researchers and stakeholders from diverse disciplines to support project delivery and research outcomes.
• Maintain accurate experimental records and ensure compliance with laboratory safety and research governance requirements.

Qualifications and Requirements

• PhD in Microbiology, Systems Biology, Biotechnology, Bioengineering, Bioinformatics, Life Sciences, or a related discipline.
• Demonstrated experience in molecular microbiology and multi-omics research methodologies.
• Proven experience in genomic, transcriptomic, fluxomic, or related omics analyses using laboratory and computational approaches.
• Experience in bioinformatics analysis of amplicon sequencing, metagenomic sequencing, or related datasets.
• Familiarity with microbial culture techniques; experience with bioreactor systems or defined culture systems would be advantageous.
• Experience in metabolic, ecological, statistical, or related modelling approaches.
• Strong written and verbal communication skills, including scientific writing and presentation abilities.
• Ability to work effectively both independently and as part of a multidisciplinary research team.
• Strong organisational skills, attention to detail, and the ability to manage multiple priorities and timelines.

Preferred Attributes

• Experience integrating and interpreting multi-omics datasets.
• Proficiency in scientific programming, computational biology, or data analysis tools relevant to bioinformatics workflows.
• Track record of scientific publications, technical reports, or research project contributions.

We regret to inform that only shortlisted candidates will be notified.