986 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" Fellowship research jobs in United States
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Jia Liu is seeking a highly-motivated postdoctoral researcher with a strong background in agentic artificial intelligence and machine learning. The successful candidate will conduct independent, high
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, and where every individual is valued. You can find these values and goals here: https://www.umass.edu/strategicplan/strategic-plan) . The University of Massachusetts Amherst welcomes all qualified
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, and Nutrition (https://www.medschool.umaryland.edu/endocrinology/) is located in the new Health Sciences Research Facility III building in Baltimore, which is equipped with state-of-the art
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systems using computer vision, quantitative image analysis, deep learning methods for detection, diagnosis, and quantitative analysis of abnormalities with multimodal data, including clinical and
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. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern machine learning methods as well as in biological data analysis are needed for the position
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February 25th, 2024 and may continue until the position is filled. Applications must be made at: http://workforum.memphis.edu . The Search Committee Chair is Dr. Subhash Jha, Associate Professor and Director
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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to cell and gene therapy. Will learn to use advanced manufacturing tools and strategies to gain a deeper understanding of challenges associated with T cell-based immunotherapies (such as CAR-T cells). Will
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. Joana C Silva, Professor at the Institute for Genome Sciences (IGS, http://www.igs.umaryland.edu ) seeks applicants for one (possibly two) postdoctoral scholar positions. IGS at the University of Maryland
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. Develop skills in coupling crop and hydrology models at watershed scales. Gain experience validating models using large, multi-source datasets. Learn to apply high-performance computing and machine learning