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, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
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). The PDRA EEO Carbon Allocation Modelling will work on the LEMONTREE (Land Ecosystem Models based On New Theory, observations and Experiments) project and will be part of a team of scientists developing
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proteins. Under the supervision of the project leader, your responsibilities will include: Establishing and optimizing cell culture protocols under sterile conditions (adherent or suspension eukaryotic cell
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Posted on Wed, 09/03/2025 - 13:09 Important Info Deprecated / Faculty Sponsor (Last, First Name): Valdez, Tulio Stanford Departments and Centers: Otolaryngology, Head & Neck Surgery Appointment
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of flotation process parameters based on experimental results. Work closely with a multidisciplinary team, including experts in mineral engineering, chemistry, and process optimization. Supervise MSc/PhD
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technologies, solar thermal integration, and system optimization. Responsibilities will include laboratory investigations, prototyping, field testing, and performance analysis of water harvesting systems across
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for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine
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optimization technologies are revolutionizing the way power grid is operated and planned. CEEESA is seeking talented and motivated researchers to enhance its capability in solving energy challenges using
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into optimization frameworks. Study the theoretical foundations of randomized algorithms in the context of sparse tensor operations and apply them to real-world datasets. Parallel Computing: Explore opportunities
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implementing an optimized, resilient, and sustainable logistics architecture for the JORF-Lasfar site. His/her work will focus on improving routing, storage, and loading flows, aiming to reduce costs, enhance