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cadre of trainees at the Center including those supported by the NIH T32 AIPrN training program. The program is designed to train the next generation of scientists and build a workforce equipped with
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, faculty members, researchers, and students are revolutionizing focus areas in advanced manufacturing, bioengineering, computational engineering, energy and the environment, product design, and robotics. In
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desired; experience performing basic laboratory procedures to process biological specimens may be desired; computer skill required with knowledge of database software applications desired. FUNCTION
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. Teamwork: Ability to work collaboratively with others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications
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interest in translational science. The postdoctoral fellow will work closely with Dr. Vivek Charu and Dr. Brooke Howitt. Required Qualifications: PhD in Biostatistics, Bioinformatics, Computational Biology
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. The investigator collaborates with interdisciplinary clinical teams to integrate these computational tools directly into hospital workflows. Routine duties include algorithm optimization and the evaluation of model
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, Maryland. About ORISE This program, administered by Oak Ridge Associated Universities (ORAU) through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and
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. Citizenship Requirements: This opportunity is available to U.S. citizens only. ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the
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, sex (including pregnancy), genetic information, age, disability, and veteran's status. As required by Title IX, UAB prohibits sex discrimination in any education program or activity that it operates
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Permanent Residents (LPR) only. This program, administered by ORAU through its contract with the U.S. Department of Energy to manage the Oak Ridge Institute for Science and Education, was established through