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preferred. Responsibilities: • Independently drive assigned projects and related experiments • Seek out new resources and learn new techniques as warranted • Present scientific work at lab meetings
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team, as well as the willingness to learn new methods and techniques and to collaborate with others as the projects evolve. Pay Range: $63,480.00 - $71,000.00. Salary will be commensurate with
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 18-Jul-26 Location: East Lansing, Michigan Type: Full-time Categories: Academic/Faculty Computer/Information Sciences
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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
focuses on developing innovative technologies to enable in vivo cell engineering (e.g., in vivo CAR T cells) for immunotherapies against cancer, autoimmune disorders, and infectious diseases. The successful
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expected to end after a 1-year contract. Renewal is dependent on the need for extension and/or if additional funding is secured to extend employment. Annual Salary: $62,232 - $71,748 | Commensurate with
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datasets to identify genetic contributors to disease risk within the All of Us Research Program secure Researcher Workbench environment using R and/or Python. 7. Develop and apply machine learning and
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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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The Office of Postdoctoral Affairs to learn more about our postdoctoral community. Resume/CV and cover letter should be included with the online application. Stony Brook University is committed to excellence
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, Skills, and Abilities Excellent written, verbal and computer skills required. Excellent communication and interpersonal skills. Must be able to work independently and/or collaboratively. Excellent critical
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic