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, optimize, and operate bioreactors, digesters, and other equipment. By employing advanced techniques like sensitivity analysis and process simulations, the candidate will improve yields and energy efficiency
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recovery strategies for emerging solar technologies. Working in state-of-the-art laboratories, you will design experiments, optimize processing conditions, characterize materials, and collaborate with
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/rDA). • Optimizing reaction conditions. • Assessing the generality of ihDA/rDA sequences. • Translating reactions into flow chemistry for real-time NMR monitoring (in collaboration with ANR SOFTNMR
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from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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organizations, or government agencies on energy or infrastructure issues. Background in digital twin platforms, cyber-physical systems, or energy system modeling and optimization. Familiarity with large-scale
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: Development and application of AI and machine learning methods for protein design Design of enzymes using computational models Identification and optimization of plastic-degrading enzymes Experimental
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candidate will work full time on the above outlined research project. It is expected that they will actively and creatively develop and optimize the detailed methods to pursue the overall project goals. All
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motivated Postdoctoral Researcher to join our Grid Planning and Analysis Center (GPAC). This position will focus on tackling critical optimization challenges in medium-term power system planning like
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, and energy efficiency will be performed to optimize desalination processes for regional sustainability. The successful applicant will oversee projects, develop extensive technical expertise, and
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on the development and analysis of continuous and discrete models in connection with convex and nonconvex optimization problems and monotone inclusion systems. Our ideal candidate already has experience with modern