-
candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage
-
to develop predictive models for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials
-
of computational tools for process monitoring and predictive analysis Candidate Criteria Applicants should have: A PhD in Process Engineering, Chemical Engineering, or a closely related field Strong expertise in
-
digital twins for industrial chemical processes Process optimization and model-based decision support tools Development of computational tools for process monitoring and predictive analysis Candidate
-
an intense of microbial activity contributes into the process of stabilization of organic matter; Assess the effects of organo-mineral management on soil biological parameters, including soil fauna; Predict
-
technologies. The candidate will work at the intersection of Artificial Intelligence, Scientific Machine Learning, and Energy Materials, contributing to the design of self-driving laboratories and no-code
-
interfaces, and condensation surfaces under varied operating scenarios. Develop and refine performance simulation models and predictive tools to support system optimization and deployment strategies. Prepare
-
; Assess the effects of organo-mineral management on soil biological parameters, including soil fauna; Predict the dynamic of OM in the future global climate change by using Soil Organic Models. Mentor
-
and develop recommendations. Area of specialization: soil microbiome analysis, general microbiology, Molecular Biology, Agronomy and, Sequence dat analysis and R coding skills Main responsibilities