French Digital Agriculture Convergence Lab: PhD positions advertised, Autumn 2018
Agriculture has to cope with the triple issue, ie being competitive, preserving the environment and offering correct living conditions to farmers. Digital technologies, eg satellite images, smartphones, connected objects, Internet of Things, big data, modelling, simulation, High-Performance Computing may help to face the challenge… However, innovation in digital agriculture is not straightforward: technology adoption is an issue and the way they can revolutionize the global value chain is not known.
#DigitAg, the “Digital Agriculture Convergence Laboratory”, has been created in 2017 in Montpellier (with some labs in Toulouse and Rennes) with the ambition to address these questions, by putting together a substantial interdisciplinary taskforce of about 300 researchers from 30 laboratories in Montpellier, Toulouse and Rennes (France). It carries out research, higher education and innovation to support the development of digital agriculture and related digital economy in France and in the Southern countries. Interdisciplinary research deals with disciplines crossing biological, agricultural, digital, economic and social sciences. #DigitAg gathers 17 partners, both public (INRA, INRIA, IRSTEA, CIRAD, Montpellier University, Montpellier Supagro, AgroParisTech Montpellier, ACTA, SATT AxLR) and private (IDATE, Smag, Vivelys, Pera-Pellenc, Agriscope, Fruition Science, ITK, Terranis). It is financially supported during 7 years by the National Research Agency, with a prisionnal funding of 9,9 M€.
#DigitAg supports a dozen of PhD grants every year, from blue sky research to applied research, as well as around 25 grants for master internships per year. #DigitAg has the ambition to host foreign students and researchers, with dedicated calls for mobility.
Doctoral thesis subjects:
1) Integrating metabolomic data by quantification of high throughput data. Application to perinatal mortality in pigs
2) Distribute durably with digital? The case of fresh agricultural and food products
3) Leverage Multi-Source Remote Sensing data via machine learning to improve Crop Monitoring Systems: a Cross-comparison between France and Senegal
6) Selecting pesticidal plants for animal and plant health in Africa using exploratory conceptual navigation
7) Applying big data methodologies to improve the chemometrics local-PLS algorithms
8) Combining Semantic Web and modelling approaches for organizing phenotyping data collected at different scales of plant organization
9) Interactive exact optimisation for numerical services to agriculture
10) Data analysis from the connected beehives of beekeepers
11) Improving innovation processes in digital agriculture
12) The Innovation System of Digital Agriculture facing the ecological transition
13) Improving food security systems by linking heterogeneous data – The case of agricultural production in West Africa
14) Quantification of pest regulation by generalist predators by analysis of image sequence to determine and quantify network of interactions, case of the banana weevil
Director of #DigitAg
More information on: www.hdigitag.fr/en/