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.

Hiring Institution: NTU

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