• Australian Institute for Bioengineering and Nanotechnology (AIBN)

• Join a university ranked in the world’s top 50

• Collaborate with highly awarded, world-class colleagues  

• Access state-of-the-art facilities to further your research endeavours 

• Based at our vibrant and picturesque St Lucia Campus

About UQ

As part of the UQ community, you will have the opportunity to work alongside the brightest minds, who have joined us from all over the world, and within an environment where interdisciplinary collaborations are encouraged.

At the core of our teaching remains our students, and their experience with us sets a foundation for success far beyond graduation. UQ has made a commitment to making education opportunities available for all Queenslanders, regardless of personal, financial, or geographical barriers.

As part of our commitment to excellence in research and professional practice in academic contexts, we are proud to provide our staff with access to world-class facilities and equipment, grant writing support, greater research funding opportunities, and other forms of staff support and development.

About This Opportunity 

Synthetic biology is characterised by a cyclic workflow based on the design, build, test, learn paradigm. The emergence of genome-foundries allows for the rapid, but still costly, generation of large numbers of engineered strains. The University of Queensland is establishing a complementary facility to genome-foundries, the Integrated Design Environment for Advanced biomanufacturing (IDEA bio, https://www.ideabio.org.au/). This facility will consist of a TEST capability that allows for a deep phenomic characterisation of mutant strains, in partnership with Queensland Metabolomics and Proteomics (Q MAP https://www.qmap.org.au/) and the Australian Genome Foundry (Macquarie University), as well as a LEARN capability that seeks to learn from large ‘omics data sets and direct strain optimisation, pathway optimisation and metabolic engineering to advance synthetic biology efforts in Australia.

We are seeking a Postdoctoral Research Fellow specialising in machine learning to join a team of researchers to establish workflows to drive strain design and bioreactor operation optimisation at this facility. The position is primarily computationally based and will work with a metabolic modeller/data scientist, bioinformatician and dedicated software engineer. Modelling and machine-learning approaches will be used to learn from large data sets to identify optimal gene up/down regulation strategies to guide further strain engineering rounds, or to guide the optimisation of bioreactor operation. The role likely requires extensive coding and workflow development, and familiarity with software engineering principles or a software engineering background is extremely favourable.

Whilst the role is academic in nature, as an employee of an NCRIS-funded facility (https://www.education.gov.au/ncris), the position has a strong service focus. You will be required to aid in the analysis, interpretation and reporting of data to clients by contractual deadlines, which may include researchers and industry, whilst developing novel workflows to allow for high-throughput data analysis.

Key responsibilities will include: 

Research

• Develop data management pipelines and computational workflows to analyse and derive insights from small to moderate data-sets containing measurements of proteins, metabolites and bioreactor performance.
• Produce quality research outputs consistent with discipline norms by publishing or presenting in high quality outlets.
• Apply machine-learning approaches to maximise learning from smaller datasets.
• Expand or parameterise mechanistic models of metabolism or bioreactors with machine-learning approaches.
• Work with colleagues in the development of joint research projects and applications for competitive research funding support.
• Contribute to progressing towards transfer of knowledge, technology and practices to research end users through translation, including commercialisation of UQ intellectual property.
• Develop a coherent research program and an emerging research profile.
• Review and draw upon best practice research methodolo