Research Fellow (Environmental Fluxomics)

About the role

NTU is seeking a Research Fellow to contribute to research on quantitative microbial analysis using multi-omics approaches. The successful candidate will support laboratory and computational research, including microbial cultivation, multi-omics data generation and analysis, bioinformatics and modelling of microbial systems. The role sits in a multidisciplinary research environment covering microbiology, systems biology, microbial ecology and related fields.

Key responsibilities

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

Required profile

• PhD in Microbiology, Systems Biology, Biotechnology, Bioengineering, Bioinformatics, Life Sciences or a related discipline.
• Demonstrated experience in molecular microbiology and multi-omics research.
• Proven experience in genomic, transcriptomic, fluxomic or related omics analyses, using laboratory and computational approaches.
• Experience in bioinformatics analysis of amplicon or metagenomic sequencing data.
• Experience in metabolic, ecological or statistical modelling.
• Familiarity with microbial culture techniques; experience with bioreactors or defined culture systems is advantageous.
• Strong written and verbal communication, organisational skills and ability to work independently and in a multidisciplinary team.

Preferred attributes

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

Only shortlisted candidates will be notified.