- Full time, fixed term until 30/06/2028
- Located at Melbourne (Bundoora) campus
- Level A Academic (research only)
- Base salary from $102,101 (step 6) plus 17% superannuation contribution
About the position
The Australian Plant Phenomics Network (APPN) was established in 2009 under the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS) to develop a globally collaborative plant phenomics capability that provides leadership in infrastructure, skills and service for agricultural research and industry to maximise the productivity in Australia’s unique and variable environment. In January 2024, La Trobe University joined as a new APPN Node, providing advanced plant phenomics services to academia and industry. The La Trobe APPN Node will exist within a cooperative national network of nine nodes that are coordinated from the APPN Central at the Adelaide University. The role requires a data scientist with experience in predictive modelling using non-invasive plant phenotyping data (multi-/hyperspectral sensor outputs).
Skills and Experience
To be considered for this position, you will have;
- Completion of a tertiary qualification related to image-focused machine learning, with at least 3 years of relevant experience, or an equivalent combination of education and/or training, including broad experience in a scientific teaching and/or research and/or industry environment(s).
- Experience in the operation, maintenance and troubleshooting of specialised imaging infrastructure, especially multi/spectral cameras.
- Experience in the maintenance and use of high-performance computing (HPC) systems, including Linux, shell, slurm and/or PBS.
- Excellent interpersonal skills with the demonstrated ability to liaise and work with diverse groups of stakeholders, including staff at senior levels, researchers, technical staff, students, and other organisations.
- Capacity to work independently as well as in a team environment.
- Demonstrated high level of proficiency with written and spoken English, including complex system documentation.
- Demonstrated expert knowledge in building and deploying machine learning algorithms for data and/or multi-/hyperspectral image analysis using supervised and unsupervised deep learning techniques.
- Demonstrated expert knowledge in programming languages and standards such as Python, R, SQL and/or JSON, and database management systems, including object stores or data lakes, that underpin contemporary research activities
- Demonstrated expert experience in data visualization for researchers, stakeholders and/or enterprise reporting and analytics (e.g. python or R libraries, PowerBI, Tableau or similar).
- Demonstrated experience in configuring and administering both SQL and Non-SQL databases and building automated pipelines around these.
Other requirements;
- Comply with the Australian Government Department of Health, Office of Drug Control guideline standards for Fit and Proper Persons and Suitable Staff https://www.odc.gov.au/; AND
- Undertake a current (within the last 12 months) national police check; AND
- The position will involve sponsored research with industry partners requiring the employee to agree to confidentiality clauses as well as assignment of Intellectual Property (IP) rights to the University. While this will not prevent publication, it may cause some delays as processes to protect IP are implemented.
Please refer to the Position Description for other duties, skills and experience required for this position.
Position Description
PD New Research Associate – Plant Phenotyping.pdf
Welcome to Bundoora campus – Please click on the video link below:
https://f.io/KDo0ceng
LTU Masterplan
https://youtu.be/VIDo4IoDD0k
Benefits
We offer a wide range of benefits and entitlements to staff members at La Trobe.
Click HERE to find out more.
How to apply
Closing date: By 11:55pm Monday 2nd March 2026
Position Enquiries: Mathew Lewsey, Professor
Email: M.Lewsey@latrobe.edu.au
Recruitment Enquiries: Yola El-hassanieh, Talent Acquisition Operations Officer
Email: Y.El-hassanieh@latrobe.edu.au
Only candidates with Full Working Rights and residing in Australia may apply for this position.
Please submit an online application ONLY and must include the following documents to be considered:
- Responses to all the Key Selection Criteria under Essential Criteria in the PD;
- 1 page Cover letter; and
- An up to date resume
Please scroll down to apply.
Aboriginal and Torres Strait Islander Applicants
We welcome and strongly encourage applications from Aboriginal and Torres Strait Islander people.
La Trobe University is committed to creating a diverse and inclusive workforce. We take an intersectional approach by actively supporting and encouraging people of all backgrounds and abilities to submit an application and aim to ensure that the recruitment and employee experience is as accessible and inclusive as possible. Flexibility in interview format will be offered to shortlisted candidates.
All La Trobe University employees are bound by the Working with Children Act 2005. If you are successful, you will be required to hold a valid Victorian Employee Working with Children Check prior to commencement.
Why La Trobe:
- Develop your career at an innovative, global university where you’ll collaborate with community and industry to create impact.
- Enjoy working on our inspiring and stunning campuses – the perfect hub for industry, students and academics
- Help transform the lives of students, partners and communities now and in the future
La Trobe’s Cultural Qualities:
La Trobe University is committed to upholding the National Code to Prevent and Respond to Gender-Based Violence (GBV Code). This aligns with our mission to create safe and respectful communities. Candidates will be asked during the recruitment process to declare whether they have ever been investigated for, or found to have engaged in, gender-based violence in previous employment and/or in legal proceedings and provide relevant information to assist in determining suitability. Gender-based violence means any form of physical or non-physical violence, harassment, abuse or threats based on gender, that results in, or is likely to result in harm, coercion, control, fear or deprivation liberty or autonomy.
