The Massey University is pleased to offer the PhD Position: Characterizing Honey Composition. The program is open to students who have a master’s degree (or equivalent) in food or process engineering, computational science or similar discipline with a focus on applied mathematics and computing.

The eligible candidates will work in a research team drawn from the School of Food and Advanced Technology, the Massey AgriTech Partnership, AgResearch, and the project’s industry partners. They will work mainly on the research-intensive and beautiful Palmerston North campus, amongst a vital team of professors, young researchers and PhD students.

Massey University is the only university in New Zealand offering a range of undergraduate and postgraduate degrees, diplomas and certificates to students from around New Zealand, and the world.

Scholarship Description:

• Applications Deadline: Closed
• Course Level: PhD
• Study Subject: Food Science, Spectroscopy, Machine Learning & Artificial Intelligence
• Scholarship Award: The successful candidate will receive a FIET scholarship covering fees and stipend for three years.
• Nationality: Internationally
• Number of Scholarships: Not given
• Scholarship can be taken in New Zealand, Palmerston North

Eligibility for the Scholarship:

To be eligible, the applicants must be following all the given criteria:

• Eligible Countries: Specifically not given, contact employer
• Entrance Requirements:
• Master’s degree (or equivalent) in food or process engineering, computational science or similar discipline with a focus on applied mathematics and computing.
• Familiarity with at least one programming language (e.g., R, Matlab Python).
• Experience in data and image analysis, ideally machine vision techniques.
• Required personal skills
• The ability for independent work displaying initiative and careful thought
• The analytical and academic approach to research questions
• Good collaborative/social skills
• Proficiency in English, both written and spoken

Application Procedure:

To apply, the applicants must send your CV and cover letter in a single PDF to Dr Reddy Pullanagari,
[email protected] with the subject “Characterising honey composition by hyperspectral analysis PhD position”.

• Predictions using known honey samples under laboratory conditions. Several hundred known honey samples are available for inspection using several hyperspectral cameras to develop efficient predictions based on a few spectral lines. Different data mining techniques may be explored to develop robust prediction models.
• Application of predictions to whole frames in the laboratory setting: Image processing techniques will be needed to isolate pixels for an individual cell, a task supported by a post-doctoral researcher also working in the project. The PhD will determine how best to use data from pixels allocated to a cell.
• Development of a prototype for use in the industrial setting: The PhD researcher will assist the post-doctoral fellow to develop an industrial unit by applying the predictive tools developed. The PhD would address more fundamental issues and the post-doc address more applied ones.
• Fluorescence: The phase addresses how best to use the hyperspectral camera to capture the fluorescence signature cell by cell. This will require special illumination and may need a sequence of illuminations and image captures, thus introducing a temporal element to the technique.

Scholarship Link