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or translational research optimizing advanced water treatment processes (e.g., reverse osmosis) to reduce costs and emissions while providing safe resilient supply. They should have documented experience with a
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challenge for artificial intelligence. Our lab’s research is driven by the observation that, in practice, there is often a wealth of data specific to the application domain that can be leveraged to optimize
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Biodiversity at Stanford's Hopkins Marine Station to expand functional genomic tools into new marine invertebrate species! We seek a highly motivated Postdoctoral Researcher to spearhead the adaptation and
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School of Medicine. The project will focus on optimization of peptide ligands targeting promising cancer antigens followed by subsequent radiolabeling and pre-clinical validation. The Beinat lab employs
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effective immunotherapeutic targets. Finally, we plan on continuing the path to clinical translation with further preclinical research (proteasome manipulation and optimization studies, bioinformatics
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later than September 1st, 2025 Has research expertise on mechanism design or optimization approaches to resource allocation. Sub-areas of interest include: Dynamic mechanism design Robust optimization and
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advancing preclinical research in ultra-high dose rate radiotherapy (FLASH RT). This position offers a unique opportunity to contribute to cutting-edge research using electron beam FLASH RT in small animal
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experience. Research background in decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow
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. Pay Range: 75,000-77,000K The Stanford Mineral-X (link is external) seeks a highly motivated and skilled postdoctoral scholar to join our research project on optimization of critical minerals
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to known toxicants leading to vascular diseases such as coronary artery disease. We are seeking a highly motivated postdoctoral research candidate with a background in molecular biology, genetics, and/or