Fisheries Scientist (Marine Ecosystem Modelling)

• Noumea-based position
• Attractive expatriate package
• Join the principal development organisation in the region

Description

The Pacific Community (SPC) is the principal scientific and technical organisation in the Pacific region, supporting development since 1947. We are an international development organisation owned and governed by our 27 country and territory members. In pursuit of sustainable development to benefit Pacific people, our unique organisation works across more than 25 sectors. We are known for our knowledge and innovation in such areas as fisheries science, public health surveillance, geoscience, and conservation of plant genetic resources for food and agriculture.

The Fisheries, Aquaculture and Marine Ecosystems (FAME) division is composed of three programmes: the Coastal Fisheries and Aquaculture Programme (CFAP); the Oceanic Fisheries Programme (OFP); and the Marine Ecosystems Programme (MEP). The Director’s Office provides implementation support and strategic direction across the three programmes and cross-cutting projects. Working with all 22 PICTs, SPC FAME has strong partnerships with regional, sub-regional and national entities working in the marine sector. SPC FAME staff are based in New Caledonia, Fiji, Federated States of Micronesia, Solomon Islands, and Tonga, with most of the staff being based in New Caledonia.

The role – the Fisheries Scientist (Marine Ecosystem Modelling) will undertake a programme of work that supports the development and application of fisheries and ecosystem population dynamics models to tuna fisheries in the western and central Pacific Ocean.  The role will have a strong focus on projecting the impact of climate change on tuna populations over seasonal, decadal and longer timeframes to assist the development of advanced warning systems and to evaluate adaptation options that mitigate adverse climate impacts on fisheries.

The key responsibilities of the role include the following:

Model development

• Contributing to the development of existing numerical model, adhering to best practices in code development and version control.
• Contributing and conducting diagnostic and analytical routines for model analyses such as sensitivity analysis, likelihood profiling, etc.
• Developing diagnostics to evaluate model performance and document them.

Apply SEAPODYM and similar models

• Developing SEAPODYM model applications by designing and running parameter estimation, performing model error analysis and model validation
• Undertaking evaluations of the impacts of current and future climate regimes on Pacific tuna population dynamics
• Assist with support/mentoring for OFP and FAME staff on models

Technical Advice

• Leading and/or contributing to scientific reports and peer-reviewed publications
• Participating, presenting in international conferences and meetings dealing with ocean ecosystem modelling, ocean climate change and ecosystem monitoring.
• Provide technical advice and respond in a timely manner to ad hoc requests for advice from partners.

Develop capabilities

• Assist in the development and delivery of workshops and training to build capacity for national and regional institutions to apply climate models to evaluate impacts on Western Central Pacific Ocean ecosystems and tuna fisheries.
• Contribute to the development of training materials.
• Effectively communicate results and advice.

For a more detailed account of the key responsibilities, please refer to the online job description.

Key selection criteria

Qualifications

• PhD in Applied Mathematics, Mathematical Ecology or a related field with a background in modelling and numerical analysis or equivalent body of knowledge and experience

Technical expertise

• A minimum of three years of experience of developing quantitative process-based spatiotemporal models of top predator pelagic species
• Knowledge and understanding of partial differential equations, their analytical and numerical solutions.
• Knowledge and practical experience in solving optimization problems.
• Knowledge of statistical methods for data integration and analysis.
• Knowledge of programming language(s) applied to numerical problems.
• Programming experience in R or Python, or similar high-level language for manipulating large volumes of data
• Linux computing environment

Language skills

• Ability to write academic texts in English.

Interpersonal skills and cultural awareness

• Proven ability to work as part of an inter-disciplinary and/or multi-cultural team

Salary, terms and conditions

Contract Duration – This contract is budgeted for 3 years and is subject to renewal depending on funding and performance.

Remuneration – the Fisheries Scientist (Marine Ecosystem Modelling) is a band 11 position in SPC’s 2025 salary scale, with a starting salary range of SDR (special drawing rights) 4,397-5,400 per month, which converts to approximately XPF 642,655-789,288 (USD 5,848-7,182; EUR 5,385-6,614). SPC salaries are not presently subject to income tax in New Caledonia. An offer of appointment for an initial contract will normally be made in the lower half of this range, with due consideration given to experience and qualifications. Progression within the salary scale will be based on annual performance reviews.

Benefits for Staff in a position advertised internationally (EPAI) whose duty station is Noumea – SPC provides housing support in Noumea. Establishment and repatriation grant, removal expenses, airfares, home leave travel, health and life and disability insurances and education allowances are available for eligible employees and their eligible dependents. Employees are entitled to 25 working days of annual leave per annum and other types of leave, and access to SPC’s Provident Fund (contributing 8% of salary, to which SPC adds a 10% contribution).

Languages – SPC’s working languages are English and French.

Recruitment principles – SPC’s recruitment is based on merit and fairness, and candidates are competing in a selection process that is fair, transparent and non-discriminatory. SPC is an equal-opportunity employer, and is committed to cultural and gender diversity, including bilinguism, and will seek to attract and appoint candidates who respect these values. Due attention is given to gender equity and the maintenance of strong representation from Pacific Island professionals.  If two interviewed candidates are ranked equal by the selection panel, preference will begiven to the Pacific Islander. Applicants will be assured of complete confidentiality in line with SPC’s private policy.

Application procedure

Closing date:  18 January 2026 – 11:00 pm (Noumea time)

Job Reference: CR000534

Applicants must apply online at http://careers.spc.int/

Hard copies of applications will not be accepted.

For your application to be considered, you must provide us with:

• an updated resume with contact details for three professional referees
• a cover letter detailing your skills, experience and interest in this position
• responses to all screening questions

Your application will be considered incomplete and will not be reviewed at shortlisting stage if all the above documents are not provided. Applicants should not attach copies of qualifications or letters of reference.

Please ensure your documents are in Microsoft Word or Adobe PDF format.

SPC does not charge a fee to consider your application and will never ask for your banking or financial information during the recruitment process.

Screening questions (maximum of 2.000 characters per question):

1. Briefly describe why understanding the impact of climate on Pacific fisheries is important to Pacific Island Nations
2. Briefly explain how model parameters (e.g., diffusion, mortality, habitat preference, or recruitment) can be estimated or constrained from observations. Which types of data are most informative, and how does parameter uncertainty affect predicted biomass distributions?
3. Assume the advection-diffusion-reaction model with age structure underestimates tuna biomass in equatorial regions where high local catches of tuna were observed. Propose possible causes related to model structure, forcing, or parameters, and outline how you would test and correct them.