Postdoctoral or Research Scientist Opportunities in Machine Learning, Deep Learning, Wildfire AI, and Atmospheric Monitoring University of Calabria in Italy

Open opportunity for postdoctoral or research scientist positions in machine learning, deep learning, wildfire AI, atmospheric monitoring, and geospatial deep learning. The poster, Khushal Das, is completing a PhD in Information and Communication Technologies at the University of Calabria, Italy, with research focused on geospatial AI for wildfire intelligence and atmospheric emissions modeling.

The research profile highlights work on interpretable spatio-temporal deep learning, hybrid ensemble frameworks, wildfire detection and forecasting, pollutant transport modeling, atmospheric forecasting, and explainable AI for environmental decision-support. Specific contributions mentioned include an explainable BiLSTM–GRU framework for wildfire occurrence/direction/distance forecasting, a Fire Exposure Index, and stable carbon isotope analysis integrated with ML for wildfire–atmosphere coupling.

This is not a formal scholarship call; it is a research opportunity / recruitment-style post inviting connections from groups working at the intersection of AI and real-world environmental problems. The poster says they are open to opportunities worldwide and are also interested in broader data science and applied ML roles across domains such as healthcare, finance, energy, and NLP.

Eligibility highlights: strong alignment with machine learning, deep learning, environmental AI, climate informatics, wildfire modeling, atmospheric science, geospatial analysis, and explainable AI. No deadline, stipend, or funding package is stated.

How to proceed: contact the poster directly by email, review the LinkedIn and Google Scholar links for background, and share relevant research interests or openings in your group. If you are hiring in these areas, this post is a direct invitation to connect.