Call for 2026-2027 project proposals under the ISA-China Joint Training and Research Centre

The International Seabed Authority (ISA) are pleased to announce the launch of the 2026-2027 Call for Project Proposals under the ISA–China Joint Training and Research Centre (JTRC). This call forms part of the JTRC Scientific Research Work Plan for 2026–2027 and aims to strengthen international scientific collaboration in support of the ISA Marine Scientific Research Action Plan and the United Nations Decade of Ocean Science for Sustainable Development.

The call invites joint research consortia composed of institutions from China and developing Member States of ISA—particularly Least Developed Countries (LDCs), Landlocked Developing Countries (LLDCs) and Small Island Developing States (SIDS)—to submit proposals under two research directions:

Direction 1: Scientific Biological Data Analysis and Management in Deep-Sea Habitats

Key activities envisioned under this direction include:

• Conduct a scientific review of biological data contained in ISA’s DeepData database, as well as a compilation of biological data publicly available from other global taxonomic databases and published peer-reviewed literature for selected priority region.
• Identify priorities for taxonomic identification and description of deep-sea species using scientific criteria underpinning spatial and non-spatial environmental management measures (e.g. biogeographic importance, ecological significance, vulnerability, connectivity, among others). Assess biodiversity metrics across the region and validate existing habitat suitability models using newly collected data.
• Develop species identification tools, such as a regional species checklist and/or catalogue as recently developed for the Clarion Clipperton Zone detailing the taxonomy, distribution, and ecological characteristics for the prioritized region such as the Indian Ocean and/or Northwest Pacific. Assess biodiversity metrics across the region and validate existing habitat suitability models using newly collected data.

The expected outcomes include:

• Technical study describing results of biological data analysis, including bio-geographic distribution and assessment of needs and priorities for taxonomic data standardization in the study region(s) and for identifying biological indicators of characteristic habitats across the region(s).
• Regional species checklists to aid in species identification and descriptions in selected regions in the Area and available for future taxonomic projects and collaborations.

Direction 2: Historical data scientific analysis, new data processing and machine learning techniques for DeepData

Key activities envisioned under this direction include:

• Data Cleaning and Validation: collaborate with ISA’s Data Management Division to access and clean historic data, identify and rectify inconsistencies, errors, and missing data points, implement robust validation processes to verify the accuracy and reliability of cleaned data sets.
• Statistical Modelling and Recommendations: Develop statistical models to analyse cleaned data sets and extract meaningful insights; Identify patterns, correlations, and anomalies within the data that will inform decision-making processes; Generate recommendations for further data quality improvements and initiatives based on statistical findings and insights.
• Digitization of Reporting Templates: Convert existing VBS scripting used in Excel macros into modern web-based JavaScript applications; Develop intuitive online web forms that replicate the functionalities of current reporting templates; Facilitate increased data submission rates through streamlined online reporting processes, ensure user-friendly interfaces accessible across various devices and browsers; Enable real-time validation during data entry to minimize errors and inconsistencies.

The expected outcomes include:

• The best available data including the historical data readily usable for scientific analysis. To improve data quality through comprehensive data cleaning, validation, and statistical modelling; to leverage the expertise of data scientists to enhance the integrity and reliability of historic data held by the ISA.
• New data mining and machine learning tools designed, utilizing Excel macros with VBS scripting and other modern tools to digitize existing reporting templates into online-based web forms, integrating modern JavaScript technologies.

Selected projects will receive financial support of up to approximately RMB 260,000 (about USD 36,600).  and will run for a maximum period of 20 months.

The deadline for submission of proposals is 30^th April 2026.

Submission details can be found here:

Call for Proposals | Annex A | Annex B

For further information, please contact: jtrc@isa.org.jm