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Peptide profiling and predictive modelling of fermented foods

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  • Full or part time
    Mr S Clerens
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

About This PhD Project

Project Description

PhD Student, Proteins & Biomaterials - AgResearch
The Riddet Institute is a world-best research centre in food and nutritional sciences, providing fundamental scientific understanding and training for a new generation of science leaders. The Institute integrates partner organisations (Massey University (host), Auckland and Otago Universities, AgResearch and Plant & Food Research) and disciplines, leading a "NZ Inc" approach to food research, and generates knowledge and capability that transforms the New Zealand food industry.

PhD project: Peptide profiling and predictive modelling of fermented foods

The role
You will be part of a multi-disciplinary project team delivering high quality science outcomes relevant to the NZ Food and Beverage industry. Embedded in a new multi-year project focused on developing novel fermented food strains, this PhD will explore the peptides and proteins in fermented foods, and use the data for predictive modelling.

Based at the AgResearch Lincoln Campus (Christchurch), you’ll be working in the Proteins & Biomaterials team under the guidance of Dr Stefan Clerens, where you will have access to advanced mass spectrometry equipment. Your university supervisor will be Prof Joanne Hort (Riddet Institute, Massey University). Biostatistics supervision will come from Dr Esther Meenken (AgResearch, Lincoln).

The project

The PhD project’s aims are (i) to perform in-depth profiling and identification of peptides from progressive fermentation time points, and conduct predictive modelling of fermentation intermediate points and end points based on earlier profiles; and (ii) to collaborate with parallel work in human taste receptor assays with the goal of using peptide profiles of fermented products to predictively model the responses of the taste receptors and humans to these products. We anticipate that techniques will include proteomics/peptidomics based on mass spectrometry, sensory evaluation and various data processing and bioinformatics software. Further, the use of statistical and other software allowing predictive mathematical modelling of fermentation, and of flavours generated in the process, will be required.

* Design and complete a PhD plan
* Carry out successful experiments
* Generate, analyse and interpret data
* Publish scientific findings
* Write and submit a PhD thesis

You will work with supervisors from AgResearch and Massey University, and will perform the majority of your research in the AgResearch laboratories in Lincoln. We offer a competitive stipend and will also cover the university’s tuition fee.

The successful candidate will have
* An undergraduate/post graduate qualification (e.g. BSc, MSc in chemistry, biochemistry or similar)
* Knowledge of molecular food science
* Background/knowledge in protein chemistry or biochemistry
* Knowledge of bioinformatics
* Experience with proteomics and/or mass spectrometry
* Knowledge of statistics, mathematical modelling, scripting or programming
* Aptitude for and interest in scientific technology
* Ability to develop collaborations and willingness to travel.

Both local and international students are encouraged to apply. Non-native English speakers must satisfy the English Language * * Requirements of Massey University in order to be considered.

How to apply
If you are interested in this opportunity, please apply on-line via the link provided and include your CV and a cover letter detailing why you feel you would be suitable for this project.

Applications close: 28th February 2018.

For more information or for a confidential discussion please contact Stefan Clerens on +64 3 321 8622 or [Email Address Removed].

This position is available from July 2018 and fixed term for three years. Applicants must be able to start work by 1 July 2018.

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