Sort by
Refine Your Search
-
for data science (Python, R, SQL, PostGIS, GeoPandas, etc.). Knowledge of urban models and spatial analysis tools (urban growth models, accessibility, change detection, etc.). Ability to work with
-
world leader in fertilizer production, is a major starter client for the University providing capital and research funds. In parallel, a new portfolio of clients is growing with the development of an R&D
-
modifications to enhance the properties of the formulations. Proactively engage in collaborative R&D by providing solutions and demonstrating the potential of formulation chemistry in addressing important
-
& Sustainable Mining institute) aims to strengthen its industrial partnerships within and beyond Morocco and Africa by adopting an integrated and sustainable strategic vision of R&D and training. The institute
-
., Bouillet, J. P., Lambais, G. R., & Le Maire, G. (2017). Importance of deep water uptake in tropical eucalypt forest. Functional Ecology, 31(2), 509-519. Cividini D., D. Lemarchand, F. Chabaux, R. Boutin, M
-
fertilizer production, is a major starter client for the University providing capital and research funds. In parallel, a new portfolio of clients is growing with the development of an R&D cluster around the
-
(especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning, particularly for multi-variable simulations. Knowledge of complex systems
-
programming (e.g., R, Python). Strong record of peer-reviewed publications in plant science or related fields. Excellent communication skills and ability to work in a collaborative, interdisciplinary team
-
gene identification (MEGARes, CARD, ResFinder). Proficiency in Python, R, or Perl, with experience in Linux/Unix environments. Solid understanding of antimicrobial resistance mechanisms, horizontal gene
-
(e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal