dear all,The University of Pisa (Italy) and the european projects SHARInG-MeD and SUS-SOIL are organising the:The School on Agriculture, Forest and Environmental Geodata Statistical Analysis, Modelling and Machine Learning [SAFEST] (2026, third edition)Venue and dates: Pisa, Italy, on campus, in Pisa, at Dipartimento di Scienze Veterinarie, viale delle Piagge, 2. [...]

Dear colleagues,We warmly invite you to submit abstracts to the following AGU26sessions on *agriculturalsystems, environmental change, and decision support*.*Abstract submission deadline: August 5, 2026*

Dear Colleagues,We would like to invite members of the DSSAT community to submit anabstract to our session at the 2026 AGU Annual Meeting, taking placeDecember 7–11, 2026, in San Francisco, California.*Session B013: **Advancing Climate-Resilient Agriculture through AI, EarthObservation, and Digital Twins*[image: 6170124c9a13d7fed13c6813ce0353c1.jpg]Best,*Meijian Yang, Ph.D.*Associate Research Scientist, PIColumbia University CCSR & NASA GISS & AgMIPAssociate Editor,* Earth's Future*

Dear DSSAT community,Varaha is hiring for two roles on our carbon and GHG modeling team:*1. Carbon and GHG Modeller * Job Description and Posting<https://jobs.pitchnhire.com/varaha.com/senior-carbon-modeller/019e3f66-72c1-73b5-b780-06c1c39cddd1>*2. Senior Carbon Modeller * Job Description and Application<https://jobs.pitchnhire.com/varaha.com/senior-carbon-modeler/019e3f66-72c1-73b5-b780-06c1c39cddd1>Moreover feel free to visit- *https://www.varaha.earth/careers<https://www.varaha.earth/careers>* for other relevant opportunitiesWe're looking for candidates with a strong background in crop/agroecosystemmodeling, soil carbon and nitrogen cycling, and greenhouse gasquantification; DSSAT experience is highly relevant to these roles. [...]

Dear Colleagues,We would like to invite members of the DSSAT community to submit an abstract to our session at the 2026 AGU Annual Meeting, taking place December 7–11, 2026, in San Francisco, California.Session GC013: AI-Ensemble Modeling of Weather Extremes on Agricultural Production SystemsCo-convened by Prof. Bruno Basso (https://www.canr.msu.edu/people/basso_bruno) and Dr. Christiana Olusegun, this session will explore how artificial intelligence and machine learning can be integrated with process-based, statistical, and ensemble modeling approaches to improve the prediction, risk assessment, and management of extreme weather impacts on agricultural systems across scales. [...]

Dear Colleagues,We would like to invite you to submit an abstract to our proposed session at the 2026 AGU Annual Meeting, to be held December 7–11, 2026, in San Francisco, California.Session B031: Crop Modeling, Data Assimilation, and Machine Learning for Agricultural Decision SupportThis session brings together researchers working at the intersection of crop modeling, e​​arth observations, data assimilation, and artificial intelligence to advance agricultural decision support. We welcome contributions on topics including: [...]

Dear DSSAT colleagues,Università Cattolica del Sacro Cuore, Piacenza campus, Italy, is offering three fully funded PhD positions in the 42nd cycle of the Agrisystem PhD programme, at the Department of Sustainable Crop Production. All three combine field agronomy, satellite and proximal remote sensing, process based modelling and machine learning.* Smart agrivoltaic systems: integrated agro-energetic modelling and control strategies for the joint optimisation of agricultural and energy production. The work includes field experiments under an operating agrivoltaic installation, microclimate and radiation measurements, process based crop modelling under dynamic shading, and the development of control strategies for tracker management. [...]

Dear Colleagues,The Agroecosystem Modeling Lab at Virginia Tech (https://you-modeling-lab.github.io/) is seeking a highly motivated PhD student to start in Spring 2027. The student will work on a USDA-NIFA project examining how agricultural diversification practices, particularly cover cropping and crop rotation, affect crop yield, soil health, and soil biogeochemical cycling. The project will combine meta-analysis, process-based agroecosystem modeling, and AI-based approaches. Applicants with experience in DSSAT or other crop or ecosystem models and AI are especially encouraged to apply. [...]

Dear DSSAT colleagues,I would like to share an upcoming international training program that maybe of interest to members of the DSSAT community.The *2nd International Training on Climate-Resilient Digital Agriculturewith Emerging Technologies* will be held at the *Asian Institute ofTechnology (AIT), Thailand*, from *5–16 October 2026*. The program isdesigned for researchers, university faculty, graduate students, extensionprofessionals, government officials, and practitioners interested inclimate-smart and digital agriculture. [...]

Dear colleagues,We would like to invite you to submit a contribution to our ResearchTopic, *“RemoteSensing and Geospatial AI for Monitoring and Prediction of HydrologicalExtremes.”*The response to this Research Topic has been highly encouraging, and we arenow entering the final phase of accepting new submissions.Hydrological extremes, including floods, droughts, and otherclimate-related events, are increasing in frequency and severity, creatingurgent challenges for water resource management, disaster preparedness, andclimate adaptation. Recent advances in satellite and airborne remotesensing, combined with geospatial artificial intelligence (AI) and machinelearning approaches, are opening new opportunities for [...]