Sort by
Refine Your Search
-
multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor
-
maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high-impact research in top-tier conferences and journals
-
, and materials characterization to join a cutting-edge research team. The project focuses on developing sustainable and optimized processes for vanadium extraction and purification, with the goal
-
experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high
-
trials under different soil and climate conditions to optimize yield and quality of various crops. A good knowledge of biostimulants and organic/inorganic additives and their mode of action to improve crop
-
monitoring and electric vehicle battery tracking. Integrate environmental and energy sensors with real-time data collection and analysis systems. Deploy prototypes in the field and optimize their performance
-
advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more of the following research areas: Development of efficient numerical linear
-
research team. The successful candidate will work on optimizing methods for nanofibers extraction from various types of biomass, focusing on the development of efficient, sustainable, and scalable processes
-
optimization of pyrometallurgical flow sheets for the production of value-added materials or metals.The selected candidate will contribute to both fundamental understanding and industrial applications of thermal
-
in Statistial models for optimizing the chemical process Skills in elemental & structural analysis using various existing techniques. Knowledge in advanced structural characterizations will be valued