Machine learning to decipher plankton big data and unravel the link between marine plankton diversity and associated ecosystem services (ML4Plankton), is a Doctoral Network project funded by the EU though the DN MSCA for 4 years (March 2027 - Feb 2031) with a total budget of over 4.4 M€.

Project summary

General context
Marine plankton is highly diverse, with millions of taxa and genes. This huge biodiversity plays a key role in providing ecosystem services to human societies, such as oxygen production, carbon export, climate regulation, or food provision. Large datasets of various types have been gathered to document marine plankton, from individuals (e.g., species occurrences, individual images) to communities (acoustic, satellite, metagenomics). Yet, these plankton "big data" are largely underexploited, while new tools from machine learning (ML) are now available to mine them. Today, the two main challenges of using ML for plankton big data are: i) to handle, combine, and decipher data of various types, and ii) to use these data to improve marine ecosystem models, especially the ones used by the IPCC and IPBES to anticipate the impact of climate change on our oceans. Hence, there is a crucial need for training a new generation of innovative doctoral candidates (DCs) at the interface of key scientific disciplines such as marine ecology, omics, imaging, satellite, acoustics, numerical modelling, climate sciences and data science, including machine learning.
Our objectives
We offer a unique international, multidisciplinary, and multisectoral high quality and innovative research and training network. It gathers European world-class research and training centres, non-governmental organisations, governmental organisations, small and medium enterprises (SMEs), and multinational companies from 6 European countries (France, Norway, United-Kingdom, Germany, Switzerland, Poland) and Canada. The non-academic partners bring expertise in plankton harvesting, fisheries management, biodiversity conservation, marine policy, biotechnologies, computer vision, data management, communication, and public engagement. The unique set of skills of our doctoral candidates will advance their careers in various sectors such as government and policy, academic research, private consultancy, SMEs or industry, including information and communication technology, and big data analytics.

ML4Plankton gathers 13 European institutions who will be recruiting our 14 Doctoral Candidates:

• Centre National de la Recherche Scientifique (CNRS) , LOCEAN-IPSL, Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques, Paris, France: Sakina-Dorothée Ayata (project coordinator), Olivier Aumont, Renaud Person;
• Sorbonne Université (SU) LOV, Villefranche-sur-mer, France: Jean-Olivier Irisson;
• Université de Lorraine (UL) LIEC, Metz, France: Martin Laviale, Jérémy Fix;
• Collecte Localisation Satellites (CLS) Toulouse, France: Laurène Merillet;
• University of York (UYORK) York, United-Kingdom: Oliver Andrews;
• Eidgenössische Technische Hochschule Zürich (ETHZ) Zürich, Switzerland: Meike Vogt;
• University of Bristol (UBRIS) Bristol, United-Kingdom: Fanny Monteiro;
• University of East Anglia (UEA) Norwich, United-Kingdom: Thomas Mock;
• Institute of Oceanology Polish Academy of Sciences (IOPAN) Powstańcow Warszawy, Poland: Emilia Trudnowska;
• The Arctic University of Norway (UiT) Tromsø, Norway: Sünnje Basedow;
• Nansen Environmental and Remote Sensing Center (NERSC) Bergen, Norway: Julien Brajard, Laurent Bertino, Annette Samuelsen;
• Institute of Marine Research (IMR) Bergen, Norway: Ketil Malde;
• Alfred Wegener Institute (AWI) Bremenhaven, Germany: Barbara Niehoff, Katja Metfies, Alexandra Kraberg, Astrid Cornils;

Please do not hesite to contact us if you want to know more!

• In spring 2027, we will be recruiting 14 Doctoral Candidates in Europe. To apply in one country, you need to have spent less than 1 year in that contry during the last 3 years (MSCA mobility rules).
• More info coming soon!

ML4Plankton will received funding from the European Union’s Horizon Programme under the Marie Sklodowska-Curie actions HORIZON-MSCA-2026-DN-01 (Grant agreement ID: XXX). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.