Ifremer - French Research Institute for Exploitation of the Sea
State University (France), Browse similar opportunities
en
State University (France), Browse similar opportunities
Reference: PV-2021-901/1
Department/Office:
Duration of contract:3 ans
Start date:
Deadline for applications:02/05/2021
The Institute and the recruiting department
A pioneer in ocean science, IFREMER’s cutting-edge research is grounded in sustainable development and open science. Our vision is to advance science, expertise and innovation to:
- Protect and restore the ocean
- Sustainably use marine resources to benefit society
- Create and share ocean data, information & knowledge.
With more than 1,500 personnel spread along the French coastline in more than 20 sites, the Institute explores the 3 great oceans: the Indian, Atlantic and Pacific oceans. A leader in ocean science, IFREMER is managing the French Oceanographic Fleet and its dedicated scientists create ground-breaking technology to push the boundaries of ocean exploration and knowledge, from the abyss to the atmosphere-ocean interface.
Well-established in the international scientific community, our scientists, engineers and technicians are committed to advance knowledge about our planet’s last unexplored frontiers. They provide the science we need for informed decision-making and public policy and they transfer this knowledge and technology to businesses to fulfill public and private needs. Core to our mission is also to strengthen public awareness about the importance of understanding the ocean and its resources, and empowering future generations of leaders through education and outreach national campaigns.
Founded in 1984, IFREMER is a French public organization and its budget approximates 240 million euros. It is operating under the joint authority of the French Ministry for Higher Education, Research and Innovation, the French Ministry for the Ecological and Solidary Transition, and the French Ministry of Agriculture and Food.
General areas of responsibility
The Environment and Resources Laboratory in Boulogne-sur-Mer (LER-BL) plays a significant role in the Observation and Monitoring of coastal ecosystems and exploited resources in the eastern English Channel and the southern bight of the North Sea, for the understanding of the ecosystem quality, structure and functions and, in support of public policies. Research and expertise activities of the LER-BL are focused on eutrophication processes and their direct or indirect consequences on the condition of the ecosystems, focusing on phytoplankton dynamics and diversity, in relation to anthropogenic impacts and the effects of climate change. LER-BL is a member of the “Campus de la Mer” Federative Structure, of the Coastal Research Infrastructure (IR ILICO). LER-BL is particularly involved in the InterReg S3 EUROHAB, H2020 JERICO S3 and CPER MARCO projects. It brings his expertise to the Ministry in charge of the Environment for the European directives and regional seas conventions.
Summary
Machine Learning and Harmful Phytoplankton: Definition of Favourable Environmental Statuses for Blooms, Bloom Dynamics, and Development of an Expert Forecasting, Warning and Decision-Making System.
Coastal marine ecosystems are evolving significantly in response to changes in the pattern and intensity of anthropogenic pressures that have been occurring for decades. The degradation and restoration trajectories no longer necessarily correspond to the expected patterns, which makes the definition of management measures very complex. This thesis aims at characterizing the dynamics of the coastal environment, and more particularly the phytoplankton’s one (including harmful or toxic blooms) in response to these pressures at different time and space scales, from recurrent to extreme events, in order to understand the associated processes and to prioritize a set of control factors and define indicators and scenarios to assess this response. The approach will therefore be to integrate methods from Machine Learning in a meta-program, enabling us (i) to optimise the multi-source and multi-scale monitoring databases via the implementation of a data completion method, (ii) to optimally define the environmental statuses and to build a learning base via the deep approach (multi-level spectral clustering) which will lead (iii) to the development of a model which will be the core for the Numerical Expert System enabling to forecast, warn and advice.
The originality of this thesis work resides in the implementation of optimised Machine Learning methods coupled with a multi-source, multi-parameter and multi-scale approach anticipating the needs of tomorrow’s Integrated Observation Systems. The proposed digital approach presents the advantage of optimising the data pre-treatment phase in order to exploit the maximum amount of available information, and even to propose series that would be unusable as is to the expert. Beyond the improvement of knowledge about the dynamics of phytoplankton blooms, HABs in particular, and of eutrophication, this thesis work should constitute an important step in adaptation to technological evolutions in relation with the Monitoring and Observation of the Maritime Environment and should enable us to propose a complete, innovative digital system combining (i) clustering of multicriteria environmental statuses, (ii) warning system and (iii) prediction system. This definition of environmental statuses and their dynamics should also enable us to improve expertise during evaluation phases of the ecological or environmental status, as defined by European directives (WFD, MSFD) or regional marine conventions (OSPAR, Barcelona). The tools developed and the results acquired will contribute to a better definition of the environmental objectives and measurement programmes, in order to minimise the direct and indirect effects of eutrophication, taking into account past and current evolutions in terms of human-caused pressures and climate change.
Key words
Machine Learning, phytoplankton, harmful algal bloom, eutrophication, integrated observation, early warning system, forecasting, environmental expertise, support of public policy.
Required Knowledge, skills, and characteristics
Specific working conditions
PhD is a real opportunity to work on Ifremer's scientific and technological priority themes. It entitle the holder to a gross monthly salary of 1900 euros for a period of 3 years, which cannot be combined with other scholarships.
How to apply for this position?
Your application file must include:
Your application must be compiled into 2 PDF files, up to 1.5 MB for each file:
In case of any problem in attaching your documents, please upload your CV on this page (this step is mandatory for your application to be considered) and send all the documents to the thesis supervisor: alain.lefebvre@ifremer.fr
The deadline for applications is 2nd May, 2021. Nevertheless, we strongly urge you to let us know as soon as possible of your intention to apply, by contacting the subject supervisor.
Doctoral students' contracts will start as of October 1st, 2021, subject to the submission of administrative documents authorizing Ifremer to recruit the doctoral student (certificate of completion of the Master 2 or engineering degree + visa for foreign doctoral students outside the EU).
How to apply for this position
Deadline for applications: 02/05/2021
All applications are processed exclusively via our website. Interested candidates can apply by clicking the “Apply” button.
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