About this role
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
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Conduct quantitative microbial research using genomic, transcriptomic, fluxomic, and other multi-omics methodologies.
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Perform molecular microbiology experiments, including microbial cultivation, sample processing, and laboratory analyses.
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Analyse and interpret biological datasets using computational and bioinformatics tools.
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Develop and apply metabolic, ecological, statistical, or related models to address research objectives.
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Support the operation and optimisation of microbial culture systems, including bioreactors and defined culture platforms where applicable.
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Prepare research reports, scientific manuscripts, presentations, and project documentation.
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Collaborate with researchers and stakeholders from diverse disciplines to support project delivery and research outcomes.
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Maintain accurate experimental records and ensure compliance with laboratory safety and research governance requirements.
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Qualifications and Requirements
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PhD in Microbiology, Systems Biology, Biotechnology, Bioengineering, Bioinformatics, Life Sciences, or a related discipline.
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Demonstrated experience in molecular microbiology and multi-omics research methodologies.
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Proven experience in genomic, transcriptomic, fluxomic, or related omics analyses using laboratory and computational approaches.
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Experience in bioinformatics analysis of amplicon sequencing, metagenomic sequencing, or related datasets.
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Familiarity with microbial culture techniques; experience with bioreactor systems or defined culture systems would be advantageous.
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Experience in metabolic, ecological, statistical, or related modelling approaches.
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Strong written and verbal communication skills, including scientific writing and presentation abilities.
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Ability to work effectively both independently and as part of a multidisciplinary research team.
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Strong organisational skills, attention to detail, and the ability to manage multiple priorities and timelines.
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Preferred Attributes
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Experience integrating and interpreting multi-omics datasets.
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Proficiency in scientific programming, computational biology, or data analysis tools relevant to bioinformatics workflows.
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Track record of scientific publications, technical reports, or research project contributions.
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We regret to inform that only shortlisted candidates will be notified.
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Hiring Institution: NTU