Junior Research Scientist in optimisation for IoT

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INRAE presentation

The French National Research Institute for Agriculture, Food, and the Environment (INRAE) is a public research establishment under the dual authority of the Ministry of Agriculture and the Ministry of Research.

INRAE is recruiting researchers by open competition and offering permanent position.

It is a major player in research and innovation created on 1^st of January 2020. INRAE is a research institute resulting from the merger of INRA and IRSTEA. It is a community of 12,000 people with more than 200 research units and 42 experimental units located throughout France.

The institute is among the world leaders in agricultural and food sciences, in plant and animal sciences, and is 11^th in the world in ecology and environment. INRAE’s main goal is to be a key player in the transitions necessary to address major global challenges. In the face of the increase in population, climate change, scarcity of resources and decline in biodiversity, the institute develops solutions for multiperformance agriculture, high quality food and sustainable management of resources and ecosystems.

Work environment, missions and activities

TSCF research unit of INRAE Clermont-Ferrand (https://www6.ara.inrae.fr/tscf/), composed of 60 people, works on the design of new technologies and agricultural materials to implement the ecological transition of agriculture. TSCF is a member of I-SITE CAP 20-25 (https://cap2025.fr/).

TSCF leads research on wireless networks for connected objects dedicated to agri-environmental management. In this area, around fifteen TSCF researchers and engineers are specialized in computer science with a solid experience in terms of interdisciplinary projects. The designed methods target the new requirement of agriculture in terms of data acquisition in a natural environment. The data collected within crops allows early detection of events such as pest attacks or water stress. Several solutions are currently being developed in TSCF to manage the energy constraints of acquisition networks, their quality of service, the implementation of intelligent behavior within communication nodes, as well as the management of collected data.
Within several collaborative projects, these new techniques make it possible to deploy and manage networks of connected objects.
These results highlighted the need to propose new methods of optimizing these data acquisition systems, aiming to improve their overall performance. In this context, you will conduct research in the field of optimization of connected object network, with the objective of increasing their performance and responding to new needs raised by the agroecological transition. The networks to be optimized may be made up of fixed (connected objects) or mobile (agricultural machines/robots) nodes. Optimizations may relate to different aspects. This may involve improving communication strategies between nodes, for example routing messages, organizing ad hoc networks, or optimizing message sending. Energy optimization will also be an important factor, in maximizing the lifespan of the network and reducing its environmental impact. Another aspect will focus on the configuration of the network, for example, by managing uncertainties, optimizing the node positions, the network or the mobile targets coverage, defining node clusters. Finally, multi-objective optimization should make it possible to take into account several criteria at the same time.

Thus, you will bring your skills to formalize and solve different aspects of these problems. In collaboration with TSCF researchers and engineers, you will develop optimization methods for wireless communications, energy management or network configuration. You will integrate into existing TSCF projects and your methods will be experimented on different agricultural applications. You integrate into a dynamic research environment. You will benefit from collaborations with the Laboratory of Computer Science, Modeling and Optimization of Systems (LIMOS) and other units of I-SITE CAP 20-25. You will be able to create links between TSCF and other laboratories in MathNum department of INRAE. You will be fully involved in the TSCF unit project, which aims in particular to develop integrated approaches for the autonomy and performance of digital technologies in the service of agroecology.

Training and skills

You hold a PhD degree or equivalent.
Having completed a thesis in the field of computer science or mathematics is highly recommended. Knowledge and experience in optimization of networks would be a plus. You will need to have demonstrated your abilities to develop and apply optimization approaches to solve practical wireless network-related problems.

You will be required to work in collaboration with an interdisciplinary group. A taste for teamwork is necessary. Certain dynamism is expected to adapt quickly and offer solutions in a changing agricultural context.

An ability to communicate effectively is also expected, through scientific publications, presentations, or reports.

Fluency in English and knowledge of French are desired, as is long-term international experience: successful candidates who have not yet gained such experience will be strongly encouraged to make a stay abroad at the end of the internship year, prepared jointly with the host team.

INRAE's life quality

By joining our teams, you benefit from:

- 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);
- parenting support: CESU childcare, leisure services;
- skills development systems: training, career advise;
- social support: advice and listening, social assistance and loans;
- holiday and leisure services: holiday vouchers, accommodation at preferential rates;
- sports and cultural activities;
- collective catering.

For international scientists: please visit your guide to facilitate your arrival and stay at INRAE.