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Field
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limited to stem cell and developmental biology, neuroscience, biochemistry, molecular and cell biology, computational biology and biomedical engineering. Research Focus ● Stem cell and developmental
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, active learning, Bayesian optimization, agentic AI, or closed-loop materials discovery. Experience in computational heterogeneous catalysis, electrocatalysis, surface science, electronic-structure analysis
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the Department of Molecular Biology and Biochemistry on Rutgers’ Busch Campus, within walking distance of research buildings for computer science and medicine as well as fundamental biology is searching for a Post
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
to sponsored research projects with industry partners; develop innovative analytical and computational methods; publish findings in leading academic journals; mentor graduate students; support graduate-level
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experimentation, advanced metallurgical characterization, and computational modeling for quantification of materials properties related to weldability and printability, and for alloy development and compositional
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models (rodent handling/surgery experience a plus). ● Familiarity with quantitative/computational approaches (e.g., R, Python, image analysis, statistics) is a plus but not required. ● Ability
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months. For a list of potential host facilities, please visit the program website . Applicants are not limited to this list. Program Provisions You will receive a competitive monthly stipend ($2,700
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. Your mentor may also be a resource for your next career step! Who is an ideal candidate? Highly motivated recent graduates who have completed a degree program in a topic applicable to marine energy
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on the Mycobacterium tuberculosis beta-lactamase BlaC and fluorogenic substrate chemistry. This position focuses on developing and optimizing diagnostic assays, with particular emphasis on reagent formulation, enzyme
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supercomputer, the world's first exascale computing system. This is a unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and