-
expertise, the work may involve wireless communications, multi-robot coordination, trajectory planning, artificial intelligence, optimization, and the experimental validation of communication-aware robotic
-
, optimization, and the experimental validation of communication-aware robotic systems. Position Requirements: Ph.D. in Robotics, Electrical Engineering, Telecommunications, Computer Engineering, Control
-
/ Deep Learning Knowledge of: Active learning, Bayesian optimization Reinforcement learning or decision-making systems Experience with: Python ecosystem (PyTorch, Scikit-learn) Data pipelines and
-
. The project focuses on developing sustainable and optimized processes for the purification of industrial acidic and complex aqueous media through the selective removal and recovery of impurities to enable
-
experimentation, modeling, simulation, and optimization of chemical processes. The successful candidate will work on the development of advanced process models combining experimental investigations with
-
a highly motivated Postdoctoral Researcher in Process/Chemical Engineering to contribute to advanced research in experimentation, modeling, simulation, and optimization of chemical processes
-
of acidic and aqueous media, impurity separation, and materials characterization to join a cutting-edge research team. The project focuses on developing sustainable and optimized processes
-
analysis (TEA). The successful candidate will: Develop innovative strategies for transforming industrial byproducts into high-performance porous adsorbent materials. Design and optimize structuring and
-
will focus on the formulation and synthesis of advanced synthetic polymers with optimized architectures and tailored functionalities for industrial applications, such as wastewater treatment, fertilizer
-
formulations, including additives, collectors, defoamers, or related specialty chemicals, is considered an asset. Familiarity with green chemistry principles, sustainable synthesis, and process optimization is