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/ Deep Learning Knowledge of: Active learning, Bayesian optimization Reinforcement learning or decision-making systems Experience with: Python ecosystem (PyTorch, Scikit-learn) Data pipelines and
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experimentation, modeling, simulation, and optimization of chemical processes. The successful candidate will work on the development of advanced process models combining experimental investigations with
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a highly motivated Postdoctoral Researcher in Process/Chemical Engineering to contribute to advanced research in experimentation, modeling, simulation, and optimization of chemical processes
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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
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to: Design, formulate, and characterize biobased materials such as hydrogels, polymers, and composites for agricultural applications. Develop and optimize protocols for the encapsulation and controlled release
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experimentation. By integrating advanced robotics, intelligent workflows, and multidisciplinary expertise, HTMR enables researchers to rapidly design, synthesize, and optimize materials and processes across fields
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multidisciplinary expertise, HTMR enables researchers to rapidly design, synthesize, and optimize materials and processes across fields such as energy, metallurgy, smart materials, chemical engineering, and
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, polymers, and composites for agricultural applications. Develop and optimize protocols for the encapsulation and controlled release of nutrients. Investigate water-use efficiency, soil moisture dynamics, and
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optimize laboratory protocols for characterization, and functional analysis of soil biology. Utilize high-throughput sequencing technologies to analyze soil microbiomes and interpret the data using